The Senior Director, Oncology Cell and Gene Therapy Regulatory Affairs, leads the development and implementation of the global regulatory strategy for CGT products of high complexity and visibility and may serve as Franchise GRL on complex programs with multiple indications.

In addition to GRL responsibilities, the Sr RAD has the ability to function in dual capacity by also serving as a regional lead based on their location.

The Sr RAD ensures that the regulatory strategy is designed to deliver efficient approval with competitive labelling in keeping with the properties of the product(s) and the needs identified by the business, markets and patients.

The Sr RAD provides team leadership and participates in coaching and mentorship to members of the relevant CGT Global Regulatory Strategy Team and is responsible for leading the global regulatory deliverables in line with GPT goals.

The Sr RAD establishes external relationships with key Regulatory stakeholders, leveraging these to maintain competitive advantage.

They are viewed as a Senior Leader within the Regulatory Community.

Key Responsibilities:

• Lead and own the development and implementation of the global regulatory strategy for a CGT product of high complexity, from current stage through BLA submission.

• May serve in dual-role as GRL and regional RAD.

• As a core member of the global product team, ensure that regulatory strategies are designed to deliver an efficient path to approval with competitive labeling in keeping with the properties of the product(s) and the needs identified by the business, markets and patients, and contribute to governance presentations.

• Lead regulatory strategy for all health authority meetings, responses to information requests, BLA development and submission, expedited pathway designations.

• Maintain a strong working knowledge of the relevant disease areas: early- and late-stage multiple myeloma.

• Lead a Global Regulatory Strategy Team (GRST) responsible for specific indications/programs within the franchise, key contributing members from the regions, emerging markets, RA CMC, Labeling and members of the submission and execution team.

• Participate in coaching and performance feedback to members of your GRST.

• Lead the objective assessment of emerging data against aspirations and update senior management on project risks/mitigation activities.

• Represent Regulatory Affairs on Global Product Teams (GPTs) providing strategic Regulatory advice and accountable for all Regulatory activities

• Accountable for the delivery of all project-related regulatory milestones, including assessment of the probability of regulatory success and mitigations.

• You will lead preparation of the regulatory strategy document and target product labeling.

• Demonstrate strategic, leadership, and collaboration skills, contributing to effective cross-functional teamwork in product development.

• Lead, participate, and promote non-project functional or cross-functional initiatives and engage externally on the corresponding topics as needed.

• Lead the development of novel regulatory tools and technology.

• Ensure appropriate planning and construction of the global dossier and core prescribing information led by the respective teams.

• Accountable for product maintenance and compliance activities associated with marketed brands.

• Partner with marketing companies (countries) and regional regulatory affairs staff to influence developing views/guidance.

• May have line management responsibilities in addition to matrixed supervisory, leadership, and mentoring roles.

Education, Qualifications, Skills and Experience

Essential:

• An advanced degree in a science related field and seven-ten years of experience and/or appropriate knowledge/experience.

• Demonstrated success in cell and/or gene therapy regulatory strategy.

• Deep understanding of global regulatory science and integration with program strategy.

• Long standing experience of overall drug/biologic development processes and strategies for high profile, complex or novel development programs.

• Experience with product development for multiple myeloma.

• Broad background of experience working in pharmaceutical business and prior experience in several areas within regulatory affairs.

• Experience in Oncology (small molecules & biologics) is preferred.

• Proven experience leading regulatory and cross-functional teams, and stakeholder management.

• Ability to think strategically and critically and evaluate risks to regulatory activities.

• Previous experience in leading major Health Authority interactions.

• Excellent oral, written, and presentation skills.

• Strong organizational skills.

• Ability to work in a fast-paced environment in a hands-on fashion.

• Flexible and proactive, with the ability to manage multiple projects and successfully adapt to changing business needs and priorities.

Desirable:

• Successful leadership of at least one global regulatory approval including leading response team and labeling negotiations

• Experience with FDA advisory committee and EMA oral explanation .

• Experience developing products for the treatment of autoimmune conditions.

• Experience working on due diligence activities and in a business alliance environment.

• Experience in leading and growing people through coaching or mentorship.

• Contribution to non-project business initiatives (e.g. at a portfolio or cross functional level)

About AstraZeneca

At AstraZeneca, Regulatory professionals help turn breakthrough science into real solutions for patients with serious diseases by shaping innovative pathways through complex global requirements.

Working with colleagues across locations, therapy areas and external partners, this role offers the chance to influence strategy end-to-end, from early development through rapid global approvals, while learning from leading experts, sharing best practices and using data, technology and modern approaches to reduce barriers for patients worldwide.

If this opportunity to drive transformative cell and gene therapies towards approval resonates, apply now to join us in bringing life-changing medicines to those who need them most.

Competitive salary and benefits package on offer:

Recognizing the importance of individualized flexibility, our ways of working allow employees to balance personal and work commitments while ensuring we continue to create a strong culture of collaboration and teamwork by engaging face-to-face in our offices 3 days a week.

The annual base salary for this position ranges from $218,058.40 - 327,087.60. However, base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience.

In addition, our positions offer a short-term incentive bonus opportunity; eligibility to participate in our equity-based long-term incentive program (salaried roles) or to receive a retirement contribution (hourly roles).

Benefits offered included a qualified retirement program [401(k) plan]; paid vacation and holidays; paid leaves; and, health benefits including medical, prescription drug, dental, and vision coverage in accordance with the terms and conditions of the applicable plans.

Additional details of participation in these benefit plans will be provided if an employee receives an offer of employment.

If hired, employee will be in an “at-will position” and the Company reserves the right to modify base salary (as well as any other discretionary payment or compensation program) at any time, including for reasons related to individual performance, Company or individual department/team performance, and market factors.

Date Posted 10-Apr-2026 Closing Date 29-Apr-2026 Our mission is to build an inclusive environment where equal employment opportunities are available to all applicants without regard to race, color, religion, gender, sexual orientation, gender identity, age, disability, marital status, citizenship, national origin, or veteran status.

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As a hands-on contributor to the core systems that ensure the safety, reliability, and continuous improvement of LLM-powered workflows and agents for the enterprise, you will partner with Scale's Operations team and enterprise customers to translate ambiguity into structured evaluation data. This involves guiding the creation and maintenance of gold-standard human-rated datasets and expert rubrics that anchor AI evaluation systems.

Your responsibilities will also include analysing feedback and collected data to identify patterns, refine evaluation frameworks, and establish iterative improvement loops that enhance the quality and relevance of human-curated assessments. You will design, research, and develop LLM-as-a-Judge autorater frameworks and AI-assisted evaluation systems, including creating models that critique, grade, and explain agent outputs.

To succeed in this role, you will need a strong foundational knowledge of large language models, a passion for tackling complex evaluation challenges, and the ability to thrive in a dynamic, fast-paced research environment. You should be able to think outside the box, stay current with the latest literature in AI evaluation, and be passionate about integrating novel research ideas into our workflows to build best-in-class evaluation systems.

In addition to your technical expertise, you will need excellent communication and collaboration skills, as you will work closely with cross-functional teams to drive project success.

If you are a motivated and detail-oriented individual with a passion for AI research and evaluation, we encourage you to apply for this exciting opportunity.

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As a Research Scientist Manager, you will lead a world-class team of research scientists and engineers, defining the research roadmap and driving execution from early prototyping to deployment. You'll thrive in a fast-moving environment, balancing deep technical leadership with people management, vision setting, and delivery.

Key responsibilities include:

• Leading, mentoring, and growing a team of research scientists and engineers working on GenAI research initiatives
• Defining and driving a multi-year research roadmap, identifying key scientific questions, setting milestones, allocating resources, and ensuring rigorous execution
• Collaborating cross-functionally with engineering, product, client-facing teams, and external academic or industry partners to translate research into components, insights, and actionable outcomes
• Communicating compellingly, publishing research, presenting at conferences, engaging in open-source contributions, and representing the team externally
• Driving an inclusive, high-performing culture, helping your team through technical challenges, providing growth opportunities, and attracting top talent

Ideal candidates will have:

• 5+ years of hands-on research experience in machine learning, deep learning, generative models, agent/RL systems, or related domains
• A strong track record of research excellence, including publications in top-tier ML/AI venues
• Experience leading or managing research teams, mentoring, coaching, and developing talent
• Excellent written and verbal communication skills, articulating research ideas and outcomes to technical and non-technical stakeholders

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This is not a traditional analytics role. On this team, data scientists do the core statistical and modeling work, but they also build real tools and products: evaluation explorers, operator workflows, decision-support systems, experimentation surfaces, and customer-specific AI/data applications that get used in production.

The right candidate is strong in first-principles problem solving, rigorous measurement, and technical execution. They know how to define metrics, design experiments, diagnose failures, and build systems that people actually use. They are also comfortable using modern AI-assisted development tools to prototype and iterate quickly without sacrificing reliability, observability, or judgment. Python and SQL matter in this role, but as execution fluency in service of building better products and making better decisions.

Responsibilities: Partner directly with enterprise customers to understand workflows, operational pain points, constraints, and success criteria Turn ambiguous business and product problems into measurable solutions with clear metrics, technical designs, and deployment plans Design and build internal and customer-facing data products, including evaluation tools, workflow applications, decision-support systems, and thin product layers on top of data/ML systems Build end-to-end solutions across data ingestion, transformation, experimentation, statistical modeling, deployment, monitoring, and iteration Design evaluation frameworks, benchmarks, and feedback loops for ML/LLM systems, human-in-the-loop workflows, and model-assisted operations Apply rigorous statistical thinking to experimentation, causal inference, metric design, forecasting, segmentation, diagnostics, and performance measurement Use AI-assisted development workflows to accelerate prototyping and product iteration, while maintaining strong engineering discipline Diagnose failure modes across data quality, model behavior, retrieval, workflow design, and user experience, and drive fixes into production Act as the voice of the customer to Product, Engineering, and Data Science, using field learnings to shape roadmap and platform capabilities

Requirements: 5+ years of experience in data science, machine learning, quantitative engineering, or another highly analytical technical role Proven track record of shipping data, ML, or AI systems that delivered measurable business or product impact Exceptional ability to structure ambiguous problems, define the right success metrics, and translate them into executable technical plans Strong foundation in statistics, experimentation, causal reasoning, and measurement Experience building tools or products, not just analyses , for example internal workflow tools, evaluation systems, operator-facing products, experimentation platforms, or customer-specific applications Hands-on fluency in Python, SQL, and modern data/AI tooling; able to inspect data, prototype quickly, debug deeply, and productionize solutions that work Comfort using AI-assisted coding and development workflows to move from idea to usable product quickly Strong communication and stakeholder management skills; able to work effectively with customers, engineers, product teams, and executives High ownership and bias toward shipping in fast-moving environments with incomplete information

Preferred qualifications: Experience in a forward deployed, solutions, consulting, or other client-facing technical role Experience designing evaluation frameworks for LLMs, retrieval systems, agentic workflows, or other AI-enabled products Experience with large-scale data processing and distributed systems such as Spark, Ray, or Airflow Experience with cloud infrastructure and modern data platforms such as AWS, GCP, Snowflake, or BigQuery Experience building lightweight applications, APIs, internal tools, or workflow software on top of data/ML systems Familiarity with marketplace experimentation, causal inference, forecasting, optimization, or advanced statistical modeling Strong product instinct and the judgment to know when the right answer is a model, an experiment, a tool, or a workflow redesign

What success looks like: Success in this role means taking a messy, high-stakes customer problem and turning it into a deployed system that is actually used. Sometimes that system is a model. Sometimes it is an evaluation framework. Sometimes it is an operator-facing tool or a lightweight data product that changes how decisions get made. In all cases, success is defined by measurable impact, rigorous evaluation, and reliable execution.

Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You’ll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.

Salary Range: $167,200-$209,000 USD

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Your primary responsibilities will include:

• Driving research on the effectiveness and limitations of existing LLM evaluation techniques.
• Designing and developing novel evaluation benchmarks for large language models, covering areas such as instruction following, factuality, robustness, and fairness.
• Communicating, collaborating, and building relationships with clients and peer teams to facilitate cross-functional projects.
• Collaborating with internal teams and external partners to refine metrics and create standardized evaluation protocols.
• Implementing scalable and reproducible evaluation pipelines using modern ML frameworks.
• Publishing research findings in top-tier AI conferences and contributing to open-source benchmarking initiatives.
• Mentoring and guiding research scientists and engineers, providing technical leadership across cross-functional projects.
• Staying deeply engaged with the ML research community, tracking emerging work and contributing to the advancement of LLM evaluation science.

The ideal candidate will have 5+ years of hands-on experience in large language model, NLP, and Transformer modeling, in the setting of both research and engineering development.

You will thrive in a high-energy, fast-paced startup environment and be ready to dedicate the time and effort needed to drive impactful results.

Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training.

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This role requires 5+ years of experience in chief-of-staff, program management, operations, or similar roles in a research, technical, or fast-moving environment.

Key responsibilities include:

• Scope, plan, and drive model evaluation projects end-to-end
• Manage external research collaborators
• Synthesize complex information into decision-relevant inputs for leadership
• Identify new projects the company should take on
• Run the Alignment team offsite and similar events

Strong candidates may also have experience working directly with researchers, especially in AI safety or machine learning, and familiarity with the AI safety research landscape, key organizations, and ongoing debates.

Annual compensation range: $210,000-$290,000 USD.

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We're seeking a Tech Lead Manager to lead a talented team of research scientists and research engineers focused on developing and implementing novel evaluation methodologies, metrics, and benchmarks to assess the capabilities and limitations of our cutting-edge LLMs.

Key responsibilities:

• Lead a team of highly effective research scientists and research engineers on LLM evals.
• Conduct research on the effectiveness and limitations of existing LLM evaluation techniques.
• Design and develop novel evaluation benchmarks for large language models, covering areas such as instruction following, factuality, robustness, and fairness.
• Communicate, collaborate, and build relationships with clients and peer teams to facilitate cross-functional projects.
• Collaborate with internal teams and external partners to refine metrics and create standardized evaluation protocols.
• Implement scalable and reproducible evaluation pipelines using modern ML frameworks.
• Publish research findings in top-tier AI conferences and contribute to open-source benchmarking initiatives.

Ideal candidate has 5+ years of hands-on experience in large language model, NLP, and Transformer modeling, in the setting of both research and engineering development. Experience supporting and leading a team of research scientists and research engineers is also required.

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At Scale, our mission is to accelerate the development of AI applications. We're looking for a Machine Learning Research Scientist/Engineer to join our team and help us shape the future of AI.

This role operates at the forefront of AI research and real-world implementation, with a strong focus on reasoning within large language models (LLMs). You will study the data types critical for advancing LLM-based agents, including browser and software engineering (SWE) agents. You will play a key role in shaping Scale's data strategy by identifying the most effective data sources and methodologies for improving LLM reasoning.

Success in this role requires a deep understanding of LLMs, planning algorithms, and novel approaches to agentic reasoning, as well as creativity in tackling challenges related to data generation, model interaction, and evaluation. You will contribute to impactful research on language model reasoning, collaborate with external researchers, and work closely with engineering teams to bring state-of-the-art advancements into scalable, real-world solutions.

Responsibilities

• Study the data types critical for advancing LLM-based agents, including browser and software engineering (SWE) agents
• Shape Scale's data strategy by identifying the most effective data sources and methodologies for improving LLM reasoning
• Contribute to impactful research on language model reasoning
• Collaborate with external researchers
• Work closely with engineering teams to bring state-of-the-art advancements into scalable, real-world solutions

Requirements

• Practical experience working with LLMs, with proficiency in frameworks like PyTorch, JAX, or TensorFlow
• A track record of published research in top ML and NLP venues (e.g., ACL, EMNLP, NAACL, NeurIPS, ICML, ICLR, CoLLM, etc.)
• At least three years of experience solving complex ML challenges, either in a research setting or product development, particularly in areas related to LLM capabilities and reasoning
• Strong written and verbal communication skills, along with the ability to work effectively across teams

Nice to Have

• Hands-on experience fine-tuning open-source LLMs or leading bespoke LLM fine-tuning projects using PyTorch/JAX
• Research and practical experience in building applications and evaluations related to LLM-based agents, including tool-use, text-to-SQL, browser agents, coding agents, and GUI agents
• Experience with agent frameworks such as OpenHands, Swarm, LangGraph, or similar
• Familiarity with advanced agentic reasoning techniques such as STaR and PLANSEARCH
• Proficiency in cloud-based ML development, with experience in AWS or GCP environments

Benefits

• Comprehensive health, dental and vision coverage
• Retirement benefits
• A learning and development stipend
• Generous PTO
• Commuter stipend

Salary Range

$252,000-$315,000 USD

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This is a highly specialized role sitting at the intersection of model behaviour and product quality. You'll be the expert on how Claude behaves inside Claude Code, owning and maintaining the system prompts that ship with each new model snapshot. When a new model drops, you're the person making sure Claude Code feels right within days , not weeks.

You'll work closely with Model Quality and Research to understand emergent behaviours and behavioural regressions, and with product and safeguards teams to respond quickly when something goes wrong.

This role requires someone who can move fast on behavioural tuning while maintaining rigor, and who cares deeply about the end-to-end developer experience Claude Code delivers. You'll need strong prompting skills, excellent judgment about model behaviours, and the collaborative skills to work across product, safeguards, and research teams.

Responsibilities:

• Own Claude Code's system prompts for each new model snapshot, ensuring behaviours feel consistent and well-tuned
• Review production prompt changes and serve as a resource for particularly challenging prompting problems involving alignment and reputational risks
• Lead incident response for behavioural and policy concerns, coordinating with product and safeguards teams
• Scale prompting and evaluation best practices across claude code and product teams.
• Deliver product evaluations focused on model behaviours
• Define and streamline processes for rolling out prompt changes, including launch criteria and review practices
• Create model-specific prompt guides that document quirks and optimal prompting strategies for each release
• Collaborate with product teams to translate feature requirements into effective prompts

You may be a good fit if you:

• Are a power user of agentic coding tools and have strong intuition about model capabilities and limitations
• Thrive in high-intensity environments with fast iteration cycles
• Take full ownership of problems and drive them to completion independently
• Are skilled at creating and maintaining behavioural evaluations
• Have strong technical understanding, including comprehension of agent scaffold architectures and model training processes
• Are an experienced coder comfortable working in Python and Typescript
• Have independently driven changes through production systems with strong execution and responsiveness
• Have experience translating user feedback and product needs into coherent prompts and behavioural specifications
• Excel at working across organisational boundaries, collaborating effectively with teams that have differing goals and perspectives
• Have experience translating user feedback and behavioural observations into coherent prompt changes and specifications
• Care deeply about AI safety and making Claude a healthy alternative in the AI landscape

Annual compensation range for this role is $300,000-$405,000 USD.

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For example, you might do any or all of the following:

• Design and build harnesses to test AI models and systems (including agents) for dangerous capabilities such as security vulnerability exploitation, CBRN uplift, and other high-risk activities;

• Work with government agencies or other labs to collectively scope and design evaluations to measure and mitigate risks posed by advanced AI systems;

• Publish evaluation methodologies and write technical reports for policymakers.

We are seeking talented researchers to join us in shaping this vision.

Ideally you'd have:

• Commitment to our mission of promoting safe, secure, and trustworthy AI deployments in the industry as frontier AI capabilities continue to advance;

• Practical experience conducting technical research collaboratively. You should be comfortable building and instrumenting ML pipelines, writing evaluation harnesses, and quickly turning new ideas from the research literature into working prototypes;

• A track record of published research in machine learning, particularly in generative AI;

• At least three years of experience addressing sophisticated ML problems, whether in a research setting or in product development;

• Strong written and verbal communication skills to operate in a cross-functional team.

Nice to have:

• Experience in crafting evaluations and benchmarks, or a background in data science roles related to LLM technologies;

• Experience with red-teaming or adversarial testing of AI systems;

• Familiarity with AI safety policy frameworks (e.g., NIST AI RMF, EU AI Act, Korea AI Basic Act).

Our research interviews are crafted to assess candidates' skills in practical ML prototyping and debugging, their grasp of research concepts, and their alignment with our organisational culture. We will not ask any LeetCode-style questions. If you’re excited about advancing AI safety and contributing to our mission, we encourage you to apply, even if your experience doesn’t perfectly align with every requirement.

Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity-based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You’ll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.

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Key responsibilities include:

• Owning the creation of model evaluation from initial hypothesis, data scraping to final publication.
• Deeply analysing why the model failed and identifying semantic patterns, edge cases, and systemic hallucinations in raw model outputs.
• Reviewing raw data sets, meeting transcripts, and research notes to identify the 'so what' and turning these findings into a logical hierarchy.
• Acting as the bridge between the data and the narrative by structuring findings into a logical hierarchy where the most critical 'hook' lands first, followed by the supporting evidence.

As a successful candidate, you will have 5-10 years of experience in DS, ML, AI research and analysis, be a structured thinker, have a high tolerance for ambiguity, and possess executive presence. Experience in Model Evaluation, ML Engineering or Technical Research is a plus.

This role offers a competitive compensation package, including base salary, equity, and benefits. The base salary range for this full-time position in San Francisco is $205,600-$257,000 USD.

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Your responsibilities will include developing monitoring techniques and observability methods, researching mechanisms for layered control, and designing red-team simulations to probe weaknesses in oversight and control mechanisms.

To succeed in this role, you'll need a strong background in machine learning, particularly in generative AI, and at least three years of experience addressing sophisticated ML problems. You should be comfortable designing control and monitoring experiments for AI systems, building prototype systems, and quickly turning new ideas from the research literature into working prototypes.

In addition to your technical expertise, you'll need strong written and verbal communication skills to operate in a cross-functional team.

This role offers a competitive salary range of $216,000-$270,000 USD, depending on location and experience, as well as equity-based compensation and benefits, including comprehensive health, dental, and vision coverage, retirement benefits, a learning and development stipend, and generous PTO.

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Lead applied ML engineering on Scale's Applied ML team, powering data infrastructure for leading agentic LLMs (ChatGPT, Gemini, Llama). You will build scalable multi-agent systems to validate agentic reasoning and behaviours, scale human expertise, and drive research into real-world agent reliability failures despite strong benchmarks, shipping production fixes.

Responsibilities

• Build and deploy multi-agent systems for agentic reasoning validation
• Develop pipelines to detect errors and scale human judgment
• Combine classical ML, LLMs, and multi-agent techniques for reliability
• Lead research into agent failure modes and ship fixes
• Use AI tools to speed prototyping and iteration
• Build data-driven evaluations and deploy rapid improvements
• Integrate systems into Scale's platform

Ideal Candidate

• PhD or MSc in Computer Science, Mathematics, Statistics, or related field
• 3+ years shipping scaled production ML systems
• Demonstrated real-world impact
• Mastery of PyTorch, TensorFlow, JAX, or scikit-learn
• Deep expertise in agentic LLMs and multi-agent systems
• Strong software engineering and microservices (AWS/GCP)
• Rapid, data-driven iteration
• Proficiency using AI tools to accelerate work
• Strong research depth with practical bias
• Excellent cross-functional communication

Nice to Have

• Experience prototyping agent evaluation/reliability systems
• Human-in-the-loop or annotation pipeline work
• Open-source contributions in agents, evaluation, or alignment
• Publications on agent reliability (NeurIPS, ICML, ICLR)

Compensation

Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity-based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.

About Us

At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications.

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Your work will focus on curating and annotating high-quality audio data to enhance Grok's global accessibility, enabling natural spoken interactions for users worldwide, bridging language barriers through accurate speech processing, and improving the AI's handling of multilingual audio nuances.

Responsibilities:

• Use proprietary software to provide labels, annotations, recordings, and inputs on projects involving multilingual audio clips, voice recordings, speech samples, and auditory elements in various languages.

• Support the delivery of high-quality curated audio data that ensures clear, natural spoken output, accurate representation of linguistic and prosodic details (such as intonation, rhythm, and accent), and professional audio standards.

• Collaborate with technical staff to develop tasks that improve AI's ability to handle speech modulation, accent variation, noise in real-world recordings, and multilingual audio processing.

• Work with technical staff to improve annotation tools for efficient audio workflows.

Basic Qualifications:

• Native proficiency in Danish with exposure to diverse accents, dialects, or regional variations.

• Proficiency in English (minimum B2 level) with clear, natural vocal delivery and pronunciation suitable for audio recording purposes.

• Strong auditory perception to identify nuances in speech, accents, pronunciation, intonation, and audio quality across languages.

• Demonstrated ability to handle multilingual audio content, including evaluating speech accuracy, cultural vocal expressions, and contextual interpretation in spoken form.

• Demonstrated ability to transcribe audio with high accuracy across accents and varying audio quality.

• Comfort providing high-quality voice recordings and feedback on audio samples in multiple languages.

• Strong comprehension skills and the ability to make independent judgments on ambiguous or varied audio material, including noisy or accented speech.

• Strong communication, interpersonal, analytical, detail-oriented, and organizational skills, with the ability to articulate audio-related feedback effectively.

• Commitment to developing AI that masters sophisticated multilingual audio capabilities.

Preferred Skills and Experience:

• Demonstration of exceptional attention to linguistic nuance, auditory detail, and data quality beyond standard transcription work.

• Deep understanding and taste of what good/useful Audio data is.

• Strong command of advanced transcription and annotation practices, including handling disfluencies, accents, and prosodic features (intonation, stress, rhythm, emotion, etc) with high consistency and accuracy.

• Background in linguistics (e.g., phonetics, phonology, sociolinguistics), speech sciences, cognitive science, or a related field, or equivalent practical experience, with demonstrated ability to analyze accent variation, pronunciation differences, and multilingual speech patterns.

• Experience working with speech/audio datasets, annotation workflows, or AI training data, including knowledge/experience with training voice models, and an understanding of how data quality impacts model performance.

• Professional experience in voice work, including voice acting, voice recording, podcasting with a measurable audience (e.g., X following), or similar audio production demonstrating attention to clarity and recording quality.

• Demonstrated ability to exercise independent judgment in ambiguous audio scenarios and make consistent, defensible annotation decisions.

• Portfolio (strongly preferred for advanced candidates): Voice samples, annotated transcripts, or audio-related work demonstrating quality, methodology, and attention to detail.

• Candidates with professional experience in voice, linguistics, speech data, or speech evaluation and research are especially encouraged to apply.

Location and Other Expectations:

• Tutor roles may be offered as full-time, part-time, or contractor positions, depending on role needs and candidate fit.

• For contractor positions, hours will vary widely based on project scope and contractor availability, with no fixed commitments required. On average, most projects may require at least 10 hours per week to deliver effectively, though this is not a fixed commitment and depends on the scope of work. Contractors have full flexibility to set their own hours and determine the exact amount of time needed to complete deliverables.

• Tutor roles may be performed remotely from any location worldwide, subject to legal eligibility, time-zone compatibility, and role-specific needs.

• For US-based candidates, please note that we are unable to hire in Wyoming and Illinois at this time.

• We are unable to provide visa sponsorship.

• For those who will be working from a personal device, your computer must be a Chromebook, a Mac with macOS 11.0 or later, or Windows 10 or later.

Compensation and Benefits:

US-based candidates: $35/hour - $45/hour depending on factors including relevant experience, skills, education, geographic location, and qualifications. International candidates: Information will be provided to you during the recruitment process.

Benefits vary based on employment type, location, and jurisdiction. Benefits for eligible U.S.-based positions include health insurance, 401(k) plan, and paid sick leave. Specific details and role-specific information will be provided to you during the interview process.

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You will work across the full agent lifecycle,from model and system design to evaluation, deployment, and iteration,bridging cutting-edge agentic techniques with the constraints and requirements of real customer environments.

Key responsibilities include:

• Design and implement end-to-end agent systems that combine LLM reasoning, tool use, memory, and control logic to solve recurring enterprise use cases.
• Build scalable, reliable agent architectures that can be deployed across many customers with varying data, tools, and constraints.
• Develop evaluation frameworks, datasets, environments, and metrics to measure agent performance, reliability, and business impact in production settings.
• Collaborate closely with product managers, customers, data annotators, and other engineering teams to translate enterprise requirements into robust agent designs.
• Productionize frontier agent techniques (e.g., planning, multi-step reasoning and tool-use, multi-agent patterns) into maintainable, observable systems.
• Own deployment, monitoring, and iteration of agent systems, including failure analysis and continuous improvement based on real-world usage.
• Contribute to technical direction and architectural decisions for general agent development best practices and methods, with increasing scope and leadership at the Staff level.

Ideal candidates will have:

• 5+ years of experience building and deploying machine learning or AI systems for real-world, production use cases.
• Strong engineering fundamentals, supported by a Bachelor’s and/or Master’s degree in Computer Science, Machine Learning, AI, or equivalent practical experience.
• Deep understanding of modern LLMs, prompt-, context-, and system-level optimization, and agentic system design.
• Proven proficiency in Python, including writing production-quality, testable, and maintainable code.
• Experience building systems that integrate models with external tools, APIs, databases, and services.
• Ability to operate in ambiguous problem spaces, balancing research-driven approaches with pragmatic product constraints.
• Strong communication skills and comfort working in customer-facing or cross-functional environments.

Nice-to-haves include hands-on experience building AI agents using modern generative AI stacks, experience with agent frameworks, orchestration layers, or workflow systems, familiarity with evaluation, monitoring, and observability for LLM-powered systems in production, and experience deploying ML systems in cloud environments and operating them at scale.

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At Labelbox, we're building the critical infrastructure that powers breakthrough AI models at leading research labs and enterprises. Since 2018, we've been pioneering data-centric approaches that are fundamental to AI development, and our work becomes even more essential as AI capabilities expand exponentially.

We're the only company offering three integrated solutions for frontier AI development:

• Enterprise Platform & Tools: Advanced annotation tools, workflow automation, and quality control systems that enable teams to produce high-quality training data at scale

• Frontier Data Labeling Service: Specialized data labeling through Alignerr, leveraging subject matter experts for next-generation AI models

• Expert Marketplace: Connecting AI teams with highly skilled annotators and domain experts for flexible scaling

Why Join Us

• High-Impact Environment: We operate like an early-stage startup, focusing on impact over process. You'll take on expanded responsibilities quickly, with career growth directly tied to your contributions.

• Technical Excellence: Work at the cutting edge of AI development, collaborating with industry leaders and shaping the future of artificial intelligence.

• Innovation at Speed: We celebrate those who take ownership, move fast, and deliver impact. Our environment rewards high agency and rapid execution.

• Continuous Growth: Every role requires continuous learning and evolution. You'll be surrounded by curious minds solving complex problems at the frontier of AI.

• Clear Ownership: You'll know exactly what you're responsible for and have the autonomy to execute. We empower people to drive results through clear ownership and metrics.

Role Overview

We’re looking for a Full-Stack AI Engineer to join our team, where you’ll build the next generation of tools for developing, evaluating, and training state-of-the-art AI systems. You will own features end to end,from user-facing experiences and APIs to backend services, data models, and infrastructure.

You’ll be at the heart of our applied AI efforts, with a particular focus on human-in-the-loop systems used to generate high-quality training data for Large Language Models (LLMs) and AI agents. This includes building a platform that enables us and our customers to create and evaluate data, as well as systems that leverage LLMs to assist with reviewing, scoring, and improving human submissions.

Your Impact

• Own End-to-End Product Features

Design, build, and ship complete workflows spanning frontend UI, APIs, backend services, databases, and production infrastructure.

• Enable Human-in-the-Loop AI Training

Build systems that allow humans to efficiently create, review, and curate high-quality training and evaluation data used in AI model development.

• Support RLHF and Preference Data Workflows

Design and implement tooling that supports RLHF-style pipelines, including task generation, human review, scoring, aggregation, and dataset versioning.

• Leverage LLMs in the Review Loop

Build systems that use LLMs to assist human reviewers,such as automated checks, critiques, ranking suggestions, or quality signals,while maintaining human oversight.

• Advance AI Evaluation

Design and implement evaluation frameworks and interactive tools for LLMs and AI agents across multiple data modalities (text, images, audio, video).

• Create Intuitive, Reviewer-Focused Interfaces

Build thoughtful, efficient user interfaces (e.g., in React) optimized for high-throughput human review, quality control, and operational workflows.

• Architect Scalable Data & Service Layers

Design APIs, backend services, and data schemas that support large-scale data creation, review, and iteration with strong guarantees around correctness and traceability.

• Solve Ambiguous, Real-World Problems

Translate loosely defined operational and research needs into practical, scalable, end-to-end systems.

• Ensure System Reliability

Participate in on-call rotations to monitor, troubleshoot, and resolve issues across the full stack.

• Elevate the Team

Improve engineering practices, development processes, and documentation. Share knowledge through technical writing and design discussions.

What You Bring

• Bachelor’s degree in Computer Science, Data Engineering, or a related field.

• 2+ years of experience in a software or machine learning engineering role.

• A proactive, product-focused mindset and a high degree of ownership, with a passion for building solutions that empower users.

• Experience using frontend frameworks like React/Redux and backend systems and technologies like Python, Java, GraphQL; familiarity with NodeJS and NestJS is a plus.

• Knowledge of designing and managing scalable database systems, including relational databases (e.g., PostgreSQL, MySQL), NoSQL stores (e.g., MongoDB, Cassandra), and cloud-native solutions (e.g., Google Spanner, AWS DynamoDB).

• Familiarity with cloud infrastructure like GCP (GCS, PubSub) and containerization (Kubernetes) is a plus.

• Excellent communication and collaboration skills.

• High proficiency in leveraging AI tools for daily development (e.g., Cursor, GitHub Copilot).

• Comfort and enthusiasm for working in a fast-paced, agile environment where rapid problem-solving is key.

Bonus Points

• Experience building tools for AI/ML applications, particularly for data annotation, monitoring, or agent evaluation.

• Familiarity with data infrastructure components such as data pipelines, streaming systems, and storage architectures (e.g., Cloud Buckets, Key-Value Stores).

• Previous experience with search engines (e.g., ElasticSearch).

• Experience in optimizing databases for performance (e.g., schema design, indexing, query tuning) and integrating them with broader data workflows.

Engineering at Labelbox

At Labelbox Engineering, we're building a comprehensive platform that powers the future of AI development. Our team combines deep technical expertise with a passion for innovation, working at the intersection of AI infrastructure, data systems, and user experience. We believe in pushing technical boundaries while maintaining high standards of code quality and system reliability. Our engineering culture emphasizes autonomous decision-making, rapid iteration, and collaborative problem-solving. We've cultivated an environment where engineers can take ownership of significant challenges, experiment with cutting-edge technologies, and see their solutions directly impact how leading AI labs and enterprises build the next generation of AI systems.

Our Technology Stack

Our engineering team works with a modern tech stack designed for scalability, performance, and developer efficiency:

• Frontend: React.js with Redux, TypeScript

• Backend: Node.js, TypeScript, Python, some Java & Kotlin

• APIs: GraphQL

• Cloud & Infrastructure: Google Cloud Platform (GCP), Kubernetes

• Databases: MySQL, Spanner, PostgreSQL

• Queueing / Streaming: Kafka, PubSub

Labelbox strives to ensure pay parity across the organization and discuss compensation transparently. The expected annual base salary range for United States-based candidates is below. This range is not inclusive of any potential equity packages or additional benefits. Exact compensation varies based on a variety of factors, including skills and competencies, experience, and geographical location.

Annual base salary range $130,000-$200,000 USD

Life at Labelbox

• Location: Join our dedicated tech hubs in San Francisco or Wrocław, Poland

• Work Style: Hybrid model with 2 days per week in office, combining collaboration and flexibility

• Environment: Fast-paced and high-intensity, perfect for ambitious individuals who thrive on ownership and quick decision-making

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You'll combine deep technical fluency with the leadership judgment needed to operate across segments, regions, and partner types,from global health foundations to leading research institutions to frontline non-profits. You'll set the vision for how we scale our expertise from a handful of flagship partnerships to an ecosystem of organisations operating as AI-native, and you'll be accountable for the team, processes, and cross-functional relationships that make that possible.

In collaboration with Beneficial Deployment’s Head of Nonprofits, Product, Engineering, Policy, and our broader GTM organisation, you'll help ensure our partners incorporate Claude into their work responsibly, effectively, and in ways that meaningfully accelerate their missions. You'll represent Anthropic as a senior technical leader on some of our most visible and consequential partnerships, while maintaining our best-in-class safety standards.

Responsibilities:

• Lead, grow, and mentor a globally distributed team of Architects supporting mission-driven non-profits across education, global health, economic mobility, and life sciences

• Set the vision, strategy, and operating model for how Applied AI shows up in Beneficial Deployments,from discovery through deployment, and from individual partnerships to ecosystem-wide infrastructure

• Establish hiring plans, team structure, and career development paths as we scale the team globally; set goals and reviews that promote growth, output, and a high bar for technical excellence

• Partner closely with segment leads and senior partner leadership to understand requirements and shape engagements on our highest-impact partnerships

• Drive the design of cohort-based accelerators, Claude Code enablement programmes, and other scalable mechanisms that multiply our impact across many organisations simultaneously

• Identify patterns across partners and segments to inform what we build at the ecosystem level,MCPs, evals, reference implementations, and shared infrastructure

• Collaborate with Product and Engineering to surface partner needs, influence roadmap, and ensure learnings from the field shape how Claude evolves

• Represent Anthropic externally with senior leaders at foundations, non-profits, research institutions, and government-adjacent organisations

• Travel to partner sites globally for workshops, technical deep dives, and relationship building

• Help shape team processes and culture as Beneficial Deployments scales, and contribute to the broader Applied AI leadership community at Anthropic

• Travel is 30-40% due to the global nature of the team (SF, NYC, London and Bengaluru) and events across Beneficial Deployments.

You may be a good fit if you have:

• 10+ years of experience in technical, customer-facing roles (Solutions Architect, Forward Deployed Engineer, Customer Engineer, Sales Engineer, or similar), with meaningful exposure to complex, high-stakes deployments

• 7+ years of engineering or technical leadership experience, preferably building and scaling customer-facing or forward-deployed teams globally

• Experience working with or inside mission-driven organisations,education, healthcare, scientific research, global development, or non-profits,and a genuine understanding of the constraints, incentives, and operating realities of these sectors

• Familiarity with common LLM implementation patterns, including prompt engineering, evaluation frameworks, agent frameworks, and retrieval systems; working knowledge of Python

• A track record of building teams in ambiguous, fast-moving environments, and comfort wearing multiple hats as the team scales

• Strong executive presence and the ability to foster deep, trusted relationships with senior partner leadership

• Excellent communication, collaboration, and coaching abilities, with a love of teaching and helping others succeed

• The ability to think holistically, identify core principles that translate across scenarios, and make ambiguous problems clear

• A passion for making powerful technology safe and societally beneficial, and for thinking creatively about risks and benefits beyond existing playbooks

Strong candidates may also have:

• Experience leading globally distributed teams across time zones and regions

• Background in philanthropy, global health, education technology, or scientific research

• Experience designing cohort-based or programmatic delivery models that scale technical expertise across many organisations

• A working understanding of emerging research in agents, evaluations, and AI safety

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As a Research Scientist/Engineer focused on honesty within the Finetuning Alignment team, you'll spearhead the development of techniques to minimize hallucinations and enhance truthfulness in language models.

Your work will focus on creating robust systems that are accurate and reflect their true levels of confidence across all domains, and that work to avoid being deceptive or misleading.

Your work will be critical for ensuring our models maintain high standards of accuracy and honesty across diverse domains.

Responsibilities

• Design and implement novel data curation pipelines to identify, verify, and filter training data for accuracy given the model’s knowledge

• Develop specialized classifiers to detect potential hallucinations or miscalibrated claims made by the model

• Create and maintain comprehensive honesty benchmarks and evaluation frameworks

• Implement techniques to ground model outputs in verified information, such as search and retrieval-augmented generation (RAG) systems

• Design and deploy human feedback collection specifically for identifying and correcting miscalibrated responses

• Design and implement prompting pipelines to generate data that improves model accuracy and honesty

• Develop and test novel RL environments that reward truthful outputs and penalize fabricated claims

• Create tools to help human evaluators efficiently assess model outputs for accuracy

Requirements

• Have an MS/PhD in Computer Science, ML, or related field

• Possess strong programming skills in Python

• Have industry experience with language model finetuning and classifier training

• Show proficiency in experimental design and statistical analysis for measuring improvements in calibration and accuracy

• Care about AI safety and the accuracy and honesty of both current and future AI systems

• Have experience in data science or the creation and curation of datasets for finetuning LLMs

• An understanding of various metrics of uncertainty, calibration, and truthfulness in model outputs

Preferred qualifications

• Published work on hallucination prevention, factual grounding, or knowledge integration in language models

• Experience with fact-grounding techniques

• Background in developing confidence estimation or calibration methods for ML models

• A track record of creating and maintaining factual knowledge bases

• Familiarity with RLHF specifically applied to improving model truthfulness

• Worked with crowd-sourcing platforms and human feedback collection systems

• Experience developing evaluations of model accuracy or hallucinations

Benefits

• Competitive compensation and benefits

• Optional equity donation matching

• Generous vacation and parental leave

• Flexible working hours

• Lovely office space in which to collaborate with colleagues

Visa sponsorship

We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

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This role focuses on pushing the frontier of reward modeling for large language models. You'll develop novel architectures and training methodologies for RLHF, research new approaches to LLM-based evaluation and grading (including rubric-based methods), and investigate techniques to identify and mitigate reward hacking. You'll collaborate closely with teams across Anthropic, including Finetuning, Alignment Science, and our broader research organization, to ensure your work translates into concrete improvements in both model capabilities and safety.

We're looking for someone who can drive ambitious research agendas while also shipping practical improvements to production systems. You'll have the opportunity to work on some of the most important open problems in AI alignment, with access to frontier models and significant computational resources. Your work will directly advance the science of how we train AI systems to be both highly capable and safe.

Responsibilities:

• Lead research on novel reward model architectures and training approaches for RLHF
• Develop and evaluate LLM-based grading and evaluation methods, including rubric-driven approaches that improve consistency and interpretability
• Research techniques to detect, characterize, and mitigate reward hacking and specification gaming
• Design experiments to understand reward model generalization, robustness, and failure modes
• Collaborate with the Finetuning team to translate research insights into improvements for production training pipelines
• Contribute to research publications, blog posts, and internal documentation
• Mentor other researchers and help build institutional knowledge around reward modeling

You may be a good fit if you

• Have a track record of research contributions in reward modeling, RLHF, or closely related areas of machine learning
• Have experience training and evaluating reward models for large language models
• Are comfortable designing and running large-scale experiments with significant computational resources
• Can work effectively across research and engineering, iterating quickly while maintaining scientific rigor
• Enjoy collaborative research and can communicate complex ideas clearly to diverse audiences
• Care deeply about building AI systems that are both highly capable and safe

Strong candidates may also

• Have published research on reward modeling, preference learning, or RLHF
• Have experience with LLM-as-judge approaches, including calibration and reliability challenges
• Have worked on reward hacking, specification gaming, or related robustness problems
• Have experience with constitutional AI, debate, or other scalable oversight approaches
• Have contributed to production ML systems at scale
• Have familiarity with interpretability techniques as applied to understanding reward model behavior

The annual compensation range for this role is $350,000-$500,000 USD.

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In this role, you'll oversee the product roadmap for your data vertical, owning 'data as a product', pipelines for data generation and quality, and researcher-facing tools that help labs train and evaluate intelligent agents in complex environments.

You'll work directly with Scale's most important customers and their leading researchers, representing Scale as the technical expert for your products and influencing both internal and external roadmaps.

The ideal candidate brings together a strong entrepreneurial & go-to-market mindset, technical depth, and a sense for AI research, enabling them to get in front of technical stakeholders to drive mission-critical outcomes.

Responsibilities:

• Own the roadmap for the Agent & RL Environment Data vertical, setting product direction and driving execution across engineering, operations, and go-to-market teams.

• Build technical partnerships with research teams at leading AI labs, identifying insights that shape new product lines and competitive strategies for your vertical.

• Design, experiment with, and deliver high-quality data pipelines, tooling, and evaluation frameworks that advance RL and agentic model capabilities.

• Scope out and scale the creation of RL environments that simulate real-world use cases.

• Collaborate cross-functionally, influencing business priorities and diving in the weeds of research, operations, and customer interactions.

Ideally, You'd Have:

• Entrepreneurial mindset: A builder excited by ambiguity and motivated to create new products from the ground up.

• 6+ years of experience in product management or a customer-facing role.

• Technical fluency: Software engineering background (a degree in computer science or equivalent experience).

• Understanding of reinforcement learnings, simulation environments, or data pipelines for model training and evaluation

• Strong customer intuition and the ability to translate technical requirements into impactful product decisions.

• Bias for action and comfort wearing multiple hats and operating in fast-moving environments.

Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training.

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For example, you might:

• Research the science of AI agent capabilities with a focus on how they relate to safety, risk factors, and methodologies for benchmarking them;
• Design and build harnesses to test AI agents' tendency to take harmful actions when pressured to do so by users or tricked into doing so by elements of their environment;
• Design and build exploits and mitigations for new and unique failure modes that arise as AI agents gain affordances like coding, web browsing, and computer use;
• Characterize and design mitigations for potential failure modes or broader risks of systems involving multiple interacting AI agents.

Ideally you'd have:

• Commitment to our mission of promoting safe, secure, and trustworthy AI deployments in the industry as frontier AI capabilities continue to advance;
• Practical experience conducting technical research collaboratively;
• Experience with post-training and RL techniques such as RLHF, DPO, GRPO, and similar approaches;
• A track record of published research in machine learning, particularly in generative AI;
• At least three years of experience addressing sophisticated ML problems, whether in a research setting or in product development;
• Strong written and verbal communication skills to operate in a cross-functional team.

Nice to have:

• Hands-on experience with agent evaluation frameworks such as SWE-bench, WebArena, OSWorld, Inspect, or similar tools;
• Experience with red-teaming, prompt injection, or adversarial testing of AI systems.

Our research interviews are crafted to assess candidates' skills in practical ML prototyping and debugging, their grasp of research concepts, and their alignment with our organisational culture. We will not ask any LeetCode-style questions. If you're excited about advancing AI safety and contributing to our mission, we encourage you to apply, even if your experience doesn't perfectly align with every requirement.

Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity-based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.

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Your North Star: Build innovative, data-driven products that enhance patient engagement and retention to improve the lives of moms and babies.

We're looking to bring on an experienced Senior Data Scientist to own the data strategy for our Growth and Patient Experience team. In this role, you will hold a dual focus: optimizing the top-of-funnel strategy to grow patient enrollment, and driving the development of next-generation products that keep those patients engaged throughout their care journey.

Responsibilities

• Become an expert in patient behavior, engagement patterns, and retention drivers, owning the team’s data science roadmap and playing a foundational role in shaping Pomelo's patient experience strategy
• Collaborate deeply with the Marketing team to build and optimize a multi-channel enrollment strategy. You will build attribution models, analyze funnel conversion rates, and identify the best ways to allocate resources towards patient enrollment.
• Define and iterate on key metrics that define the health of the business, such as enrollment and retention rates, and present insights to Pomelo’s leadership team
• Complete exploratory analyses to inform development of enrollment and engagement-focused features, such as conversation topic categorization and patient journey segmentations
• Build robust data pipelines and analytics infrastructure that connect external, marketing and product usage data, creating a unified view of the patient journey.
• Lead the team’s approach to A/B testing across marketing and product initiatives to accurately measure impact
• Collaborate closely with Product, Clinical, and Engineering teams to translate patient insights into actionable product improvements and new feature development

Requirements

• 4+ years professional experience in data science, product analytics, or data engineering
• 1+ years professional experience working in healthcare, consumer health, or high-touch consumer products
• Expert proficiency in both SQL and Python, with demonstrated ability to work across the full data stack
• Strong product sense with experience in product prototyping, A/B testing, and user behavior analysis
• Passionate about improving maternal health outcomes and creating exceptional patient experiences
• Proven track record of scoping and implementing data-driven product solutions to complex, ambiguous problems
• Comfortable leading cross-functional initiatives with Product, Engineering, and Clinical teams as a strategic partner and technical expert
• A strong communicator and a keen nose for value - someone who can easily and quickly understand the needs of different audiences
• Experience with data visualization and dashboarding tools (e.g., Looker, Tableau, Metabase)
• Experience working with modern data stack tools (e.g., dbt, Airflow, Snowflake)

Bonus Points

• Experience with AI model development including fine-tuning, prompt engineering, model evaluation and building production AI applications
• Background in healthcare AI, clinical decision support, or medical NLP

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Our Public Sector Machine Learning team is focused on deploying cutting-edge models to mission-critical government systems through products like Donovan and Thunderforge. You will take state-of-the-art models developed internally and from the community, use them in production to solve problems for our customers and taskers.

Key responsibilities include:

• Improving and maintaining production models through retraining, hyperparameter tuning, and architectural updates, while preserving core performance characteristics
• Collaborating with product and research teams to identify and prototype ML-driven product enhancements, including for upcoming product lines
• Working with massive datasets to develop both generic models as well as fine-tune models for specific products
• Building scalable machine learning infrastructure to automate and optimize our ML services
• Serving as a cross-functional representative and advocate for machine learning techniques across engineering and product organizations

Ideal candidates will have extensive experience using computer vision, deep learning, and deep reinforcement learning, or natural language processing in a production environment. Solid background in algorithms, data structures, and object-oriented programming is also required.

Nice to haves include a graduate degree in Computer Science, Machine Learning, or Artificial Intelligence specialization, experience working with cloud platforms, and familiarity with ML evaluation frameworks and agentic model design.

Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training.

You'll also receive benefits including comprehensive health, dental, and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. This role may be eligible for additional benefits such as a commuter stipend.

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Location: London, UK

Department: Sales

As the Manager of the International Partnerships, Applied AI, Solutions Architect team at Anthropic, you will drive the adoption of frontier AI by enabling the deployment of Anthropic's products (Claude for Enterprise, Claude Code, and API) through our Global and Regional System Integrators (GSIs/RSIs), cloud partners (AWS and GCP), and strategic technology partners across international markets.

Based in London, you will lead and grow a team of Partner Solutions Architects, establishing Anthropic's technical partner ecosystem across EMEA and beyond. You'll be responsible for leading & growing the International Partnerships Applied AI team, establishing processes and best practices for partner-led pre-sales engagements, helping each team member achieve success, high productivity, and career growth, and representing Anthropic as a technical lead on some of its most important international partnerships.

In collaboration with the Sales, Partnerships, Product, and Engineering teams, you'll help partners incorporate leading-edge AI systems into their practices, solutions, and customer engagements. You will employ your excellent communication skills to explain and demonstrate complex solutions persuasively to technical and non-technical audiences alike.

You will play a critical role in identifying opportunities to accelerate indirect revenue, enable partner AI practices, and execute on long-term international GTM strategy, while maintaining our best-in-class safety standards.

Responsibilities:

• Team Leadership & Development: Manage and mentor a team of Applied AI, Partner Solutions Architects, providing both technical guidance and career development. Set goals and reviews for your team, promoting growth and output

• Strategic Technical Partnership: Serve as the senior technical thought partner to the Anthropic international GTM partnerships team, providing technical expertise to better understand the partner landscape, driving key strategic programs, and identifying opportunities to deepen partner technical capabilities across international markets

• Partner Ecosystem Enablement: Embed your team with GSI and cloud partner technical teams to enable their AI practices, support troubleshooting, evangelize Anthropic in their developer communities, and serve as an escalation point for complex technical issues

• Joint Solution Development: Lead your team in collaborating with partners to identify high-value industry-specific GenAI applications, develop joint solutions, and codify reference architectures / best practices to accelerate time to deployment across international markets

• Customer Deal Support: Own the technical portions of partner-led pre-sales engagements, ensuring your team intervenes directly to unblock strategic customer deals where partners are the primary delivery vehicle, providing deep technical expertise and solution architecture guidance

• Partner Ecosystem & Events: Represent Anthropic at international partner events such as GSI customer workshops, AWS summits, and industry conferences. Lead or support partner-specific developer events, hackathons, and technical enablement sessions

• Cross-Functional Collaboration: Drive collaboration from cross-functional teams to influence and unify stakeholders at all levels of the organization to drive business outcomes. Partner closely with your aligned GTM leadership to co-build international partner strategies

• Product Feedback: Validate and gather feedback on Anthropic's products and offerings, especially as they relate to international partner use cases and deployment patterns, and deliver this feedback to relevant Anthropic teams to inform product roadmap and partner strategy

• Thought Leadership: Contribute to thought leadership through conference presentations, webinars, and technical content creation focused on the international partner ecosystem

You may be a good fit if you:

• 7+ years of experience in technical customer-facing/partner-facing roles such as Solutions Architect, Sales Engineer, Partner Sales Engineer, Technical Account Manager

• 5+ years of technical go-to-market management experience, specifically managing pre-sales or partner-facing technical teams across EMEA, APAC, and other international regions.

• Track record of successfully building and scaling partnerships with GSIs (e.g., Accenture, Deloitte, WPP, TCS, Infosys) and/or cloud providers (AWS, GCP) to solve complex technical challenges across international markets

• Experience with the unique dynamics of partner-led selling and delivery, including indirect revenue models and partner enablement at scale

• Deep technical proficiency with enterprise AI deployments, API integrations, and production LLM use cases

• Exceptional ability to build relationships with and communicate technical concepts to diverse stakeholders including C-suite executives, engineering & IT teams, and partner leadership

• Have an organizational mindset and enjoy building foundational teams in a relatively unstructured environment

• Have excellent communication, collaboration, and coaching abilities

• Are comfortable dealing with highly uncertain, ambiguous, and fast-moving environments

• Strong executive presence and ability to foster deep relationships with technical leaders and partner engineering teams

• Have at least a high-level familiarity with the architecture and operation of large language models and/or ML in general

• Experience with prompt engineering, LLM evaluation, and architecting AI-powered systems

• A love of teaching, mentoring, and helping others succeed

• Have a passion for making powerful technology safe and societally beneficial

• Think creatively about the risks and benefits of new technologies, and think beyond past checklists and playbooks

Strong candidates may have:

• Partner SA Leadership at Scale: 5+ years leading partner-facing solution architect teams through hypergrowth, with direct experience managing both senior SAs and developing junior talent in complex partner ecosystem environments

• AI/ML Technical Depth + Executive Engagement: Hands-on experience with AI/ML platforms and enterprise integration patterns, combined with proven track record engaging C-level stakeholders and partner leadership in large-scale technical evaluations and joint GTM motions

• GSI Practice Building: Experience helping GSIs or consultancies build or scale their AI/ML practices, including enablement programs, certification paths, and joint solution development

Annual compensation range for this role is £170,000-£215,000 GBP.

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Key responsibilities include:

• Painting the vision of the Figma Platform and guiding customers in realizing the value through product demonstrations and presentations
• Supporting the Sales team by addressing Figma platform questions and showcasing how Figma accelerates digital product delivery to prospective customers (pre-sales) and existing customers (post-sales)
• Owning the customer IT and Security relationship during the deal cycle by addressing security questionnaires, RFIs, RFPs, identity and enterprise questions
• Collaborating with Product and Support to identify opportunities for enhancing account security through new product features and helping influence the product roadmap
• Designing and scaling technical sales efforts, facilitating conversations and connections between our customers, sales and product teams
• Creating thoughtful content to delight customers and internal partners surrounding the Figma platform

We are looking for a fantastic life-long learner who can operate with autonomy. We'd love to hear from you if you have:

• 8+ years professional experience
• 4+ years of sales engineering or solution consulting experience in a SaaS organization
• Demonstrated ability to adapt to new technologies and learn quickly
• Responsible for positioning technology presales, successfully establishing success criteria and leading evaluations
• Familiarity with the enterprise SaaS ecosystem, front end development and product lifecycle experience

While not required, it's an added plus if you also have:

• Experience using or working with Figma, or building design systems
• You embody our values and can thrive in a constantly evolving and growing environment
• Front end development and developer lifecycle experience

At Figma, one of our values is Grow as you go. We believe in hiring smart, curious people who are excited to learn and develop their skills. If you're excited about this role but your past experience doesn't align perfectly with the points outlined in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles.

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This is a founding team: you will help us to build technical playbooks and define the processes and repeatable patterns needed for us to scale this emerging motion. You will champion our mission in the field, ensure world-class delivery, and bring insights back to our product and research teams on a regular basis.

You'll own engagements end-to-end, from SOW through production deployment. You'll work alongside Forward Deployed Engineers who build the technical solution, while you own product scoping, stakeholder management, value measurement, and the organisational complexity that comes with deploying AI agents in enterprise environments.

Responsibilities:

• Own the technical delivery plan for each engagement. Structure SOWs with clear scope, milestones, dependencies, success criteria, and value hypotheses. Translate customer business objectives into a sequenced roadmap that FDEs execute against.

• Lead technical discovery. Map customer workflows, identify constraints, define MVP scope, and shape the solution architecture for custom agent deployments.

• Run day-to-day engineering execution. Drive delivery across Anthropic and customer teams. Keep progress unblocked and sequenced. Make real-time trade-offs on scope and priority to protect the critical path.

• Own product scoping for field engagements. Define the MVP, author requirements documentation, prioritise the engineering backlog, and manage scope against success criteria as requirements evolve.

• Own the customer relationship throughout delivery. Lead executive briefings, manage stakeholder communications across technical leads and procurement, and represent Anthropic's technical credibility with senior business and engineering leaders.

• Own value measurement and ROI. Define impact hypotheses, set baselines and KPIs, run pre- and post-deployment measurement, and report outcomes to executive sponsors.

• Codify reusable delivery assets. Build solution patterns, evaluation frameworks, and technical playbooks. Extract what works across engagements and feed field signals back to Product and Research to improve our platform and models.

• Navigate enterprise and regulatory complexity. Security reviews, legal approvals, procurement processes, compliance requirements, and organisational dynamics.

• Manage scope and change. Handle evolving requirements, set expectations, negotiate contract modifications, identify risks early, and escalate with clear context when needed.

• Run delivery operations. Sprint ceremonies, milestone reviews, and progress reporting.

• Travel to customer sites. Build relationships, unblock delivery, and accelerate adoption. (25–50% expected).

You May Be a Good Fit If You:

• Have led AI/ML engagements/deployments, whether as a founder, data scientist, engineer, researcher, or in a professional services or consulting role.

• Have delivered AI, ML, or LLM-based agentic solutions into production. You understand solution patterns, integration approaches, and what breaks in real environments.

• Have experience in a specialised vertical (financial services, life sciences, pharmaceutical, retail, mining, agriculture, etc.).

• Can lead architecture discussions with engineering stakeholders, evaluate technical trade-offs, and pressure-test technical decisions. You won't write production code, but you will own the technical direction of engagements alongside FDEs.

• Have a track record delivering complex, high-stakes technical projects for enterprise clients where outcomes depended on tight coordination and fast decision-making , ideally across multiple workstreams in regulated industries.

• Have executive presence , polished, credible, and comfortable representing Anthropic to senior leaders in high-stakes environments.

• Thrive in ambiguity and bring structure where none exists.

• Have a builder's mindset , you're here to create a function, not join one.

The annual compensation range for this role is listed below.

For sales roles, the range provided is the role's On Target Earnings ('OTE') range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.

Annual Salary: $200,000-$345,000 USD

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About Anthropic

Anthropic's mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole.

About the Role

Safeguards Engineering builds and operates the infrastructure that keeps Anthropic's AI systems safe in production , the classifiers, detection pipelines, evaluation platforms, and monitoring systems that sit between our models and the real world. That infrastructure needs to be not just correct, but reliable: when a safety-critical pipeline goes down or degrades, the consequences can be serious, and they can be invisible until someone looks closely.

As a Technical Program Manager for Safeguards Infrastructure and Evals, you'll own the operational health and forward momentum of this stack. Your primary responsibility is driving reliability , owning the incident-response and post-mortem process, ensuring SLOs are defined and met in partnership with various teams, and making sure that when things go wrong, the right people know, the right actions get taken, and those actions actually get closed out.

Alongside that ongoing operational rhythm, you'll coordinate the larger platform investments: migrations, eval-platform improvements, and the cross-team dependencies that connect them. This role sits at the intersection of operations and program management. It requires genuine technical depth , you need to understand how these systems work well enough to triage effectively, judge what's actually safety-critical versus what can wait, and have informed conversations with the engineers building and maintaining them. But the core of the job is keeping the machine running well and the work moving.

What You'll Do:

• Own the Safeguards Engineering ops review
• Drive the recurring cadence that keeps the team informed and coordinated: surfacing recent incidents and failures, bringing visibility to reliability trends, and making sure the right people are in the room when decisions need to be made.
• Drive incident tracking and post-mortem execution
• Establish and maintain SLOs with partner teams
• Maintain runbook quality and incident-ownership clarity
• Drive platform migrations and infrastructure projects
• Coordinate evals platform improvements

You might be a good fit if you:

• Have solid technical program management experience, particularly in operational or infrastructure-heavy environments , you're comfortable owning a mix of ongoing operational cadences and discrete project work simultaneously.
• Understand how production ML systems work well enough to triage incidents intelligently and have substantive conversations with engineers about what's going wrong and why , you don't need to write the code, but you need to follow the technical thread.
• Are energized by closing loops. Post-mortem action items that never get done, SLOs that no one checks, runbooks that go stale , these things bother you, and you know how to build the processes and follow-ups that fix them.
• Can work effectively across team boundaries , comfortable coordinating with partner teams (like Inference) where you don't have direct authority, and skilled at keeping shared work moving through influence and clear communication.
• Thrive in environments where the work shifts between 'keep the lights on' and 'build something new' , and can context-switch between incident follow-ups and longer-horizon platform projects without dropping either.
• Have experience with or strong interest in AI safety , you understand why the reliability of a safety-critical pipeline is a different kind of problem than the reliability of a product feature, and that distinction motivates you.

Strong candidates may also:

• Have experience with SRE practices, incident management frameworks, or on-call operations at scale.
• Have worked on or with evaluation infrastructure for ML systems , understanding how evals get designed, run, and interpreted.
• Have experience driving infrastructure migrations in complex, multi-team environments , particularly where the migration touches operational systems that can't go offline.
• Be familiar with monitoring and alerting tooling (PagerDuty, Datadog, or equivalents) and the operational culture around them.

Deadline to apply: None, applications will be received on a rolling basis.

The annual compensation range for this role is listed below. For sales roles, the range provided is the role's On Target Earnings ('OTE') range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.

Annual Salary: $290,000-$365,000 USD

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A typical day in this role will involve working closely with leads to assign daily work, monitoring queues in Upwork and host/guest support cases. You will also be responsible for leading the onboarding of new properties into the Luxe category, ensuring they align with brand, design, and experience criteria. This includes conducting interviews with home consultants, completing their onboarding process, and unblocking onboarding-related challenges by collaborating with market managers and other cross-functional teams.

Your expertise will be essential in assessing walkthrough reports to determine whether a property should pass or fail Luxe criteria, providing detailed reasoning and recommendations. You will also perform visual vetting of potential Luxe listings, assessing design aesthetics, property quality, and overall luxury appeal. Additionally, you will partner with stakeholders to improve vetting frameworks, visual standards, and design benchmarks.

As a subject matter expert on Luxe design and brand positioning, you will ensure consistency across all listings. You will provide feedback and recommendations to refine property evaluation guidelines and Luxe onboarding processes. You will also mentor and coach Luxe specialists on visual assessment and luxury experience standards.

To be successful in this role, you will require a bachelor's degree or equivalent, with 6-8 years of experience in a customer experience, operations, hospitality, or design-led environment. You will also need a background in design, hospitality, architecture, or luxury segment, and proven ability to evaluate properties for luxury standards, including visual and experiential vetting.

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As an Engineering Manager, you will:

Manage the engineering team and drive technical delivery. Design, build, and optimize backend services for advanced AI-driven applications, focusing on AI agents, evaluation tooling, and automation. Comfortable working cross functionally, whether that be internal or external customers. Work across the entire product lifecycle from conceptualization through production. Build features end-to-end, system design, debugging and testing. Deliver experiments at a high velocity and level of quality to engage our customers. Influence the culture, values, and processes of a growing engineering team. Inspire and mentor engineers. Collaborating with cross-functional teams to define, design, and ship new product features and experiences.

Ideally, you'd have: At least 5 years of relevant experience and at least 2 years of experience managing back engineers is preferred. Proven success in leading, managing, and developing high-performing Engineering teams. Expertise in identifying product engagement patterns and trends for large scale consumer products. Track record of shipping high-quality products and features at scale. Desire to work in a very fast-paced environment. Ability to turn business and product ideas into engineering solutions. Excellent problem-solving skills, and be able to work independently or as part of a team.

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A typical day for this role will involve building deep expertise on Airbnb in your market/region through user research, marketplace data, and an understanding of the competitive landscape. You will work with other functional leaders in your market/region to articulate the product vision, strategy, and roadmap for Airbnb products and new businesses. You will implement best-in-class product development and management practices, maintain and articulate a product feature and roadmap prioritization plan in collaboration with local teams, and advocate for and execute new products that deliver impact for our business and users.

As the Product Manager based in our EMEA region, you will report to the Product Marketing Director for International Markets. You will be responsible for the success of Airbnb products throughout their life cycle , from concept to release. You will be the voice of our products for the market in your region and love the journey from taking a product from idea to reality.

This role is based either in London or Paris (or within easy commuting distance of these cities). The actual base pay is dependent upon many factors, such as: training, transferable skills, work experience, business needs, and market demands. The base pay range shown below is annualized, is subject to change, and may be modified in the future. This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits.

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Responsibilities: Use proprietary tools to label and evaluate data. Support and ensure the delivery of high-quality curated data. Work with engineers to refine tasks, tools, and workflows. Design, select, and refine tasks grounded in real-world occupational math, for example: Insurance and risk: premiums, deductibles, expected loss calculations, simple risk modeling. Logistics and operations: inventory and reorder policies, capacity/throughput, basic cost optimization. Skilled trades: surveying and land measurement, electrical load calculations, machining tolerances, material estimation, blueprint and scale calculations. Finance and banking: loan amortization schedules, time value of money, portfolio and risk metrics. Accounting and tax: financial statements, reconciliations, depreciation, multi-bracket tax calculations, payroll. Health and social data: rates, ratios, simple biostatistics, survey-based metrics and policy-relevant indicators. Provide detailed, step-by-step solutions and evaluate model responses for correctness, adherence to domain rules (e.g., tax codes, building codes, basic regulatory or business constraints), clarity, and plausibility. Interpret, analyze, and execute tasks based on given instructions.

Basic Qualifications: A Master's or PhD in a quantitative field such as Mathematics, Statistics, Operations Research, Economics, Finance, Actuarial Science, or a closely related discipline with strong training in applied/occupational math; or A Bachelor's degree in one of the fields above plus substantial professional experience (e.g., 2+ years) in a math-heavy occupational domain such as finance, banking, insurance, accounting, logistics/supply chain, healthcare analytics, or policy analysis Professional licensure or certification in a skilled trade (e.g., licensed surveyor, master electrician, journeyman machinist) with demonstrated expertise in trade-specific mathematical calculations. Strong proficiency in applied mathematics relevant to at least one of the above domains (e.g., probability and statistics, financial math, optimization under constraints, geometric and measurement calculations, or similar). Proficiency in reading and writing, both in informal and professional English. Strong ability to navigate various information resources and databases. Outstanding communication, interpersonal, analytical, and organizational capabilities. Solid reading comprehension skills combined with the capacity to exercise autonomous judgment even when presented with limited data/material. A strong passion for and commitment to technological advancements and innovation.

Preferred Skills and Experience: Professional certifications in relevant fields (e.g., CFA, FRM, SOA exams, CPA, Six Sigma, PE, licensed surveyor, or similar) or demonstrably equivalent experience. Prior professional experience in one or more domains such as asset management, retail or commercial banking, insurance pricing/reserving, accounting/audit, logistics/supply chain planning, healthcare analytics, public policy analysis, or skilled trades. Previous AI Tutoring experience and/or experience teaching or training others in applied or occupational math topics. Experience building and reviewing complex spreadsheets, financial or risk models, dashboards, technical drawings, or similar artifacts.

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We're hiring research engineers to define and execute the Labs research agenda. You'll scope your own projects, run experiments end-to-end, and decide when an idea is ready to hand off to a production team , or when to kill it and move on.

Responsibilities:

• Lead and contribute to research projects investigating new methods for detecting misuse of Claude, identifying malicious organisations and accounts, strengthening model safeguards, and other safety needs.

• Design and run offline analyses over model usage data to surface abuse patterns, build classifiers and detection systems, and evaluate their effectiveness.

• Develop and iterate on prototypes that could eventually feed signals into the real-time safeguards path, partnering with engineers on tech transfer.

• Contribute to a broader research portfolio investigating methods for detecting abusive behaviour in chat-based or agentive workflows, and for training the model to robustly refrain from dangerous responses or behaviours without over-refusing.

• Build evaluations and methodologies for measuring whether safeguards actually work, including in agentic settings.

• Write up findings clearly so they inform decisions across Trust & Safety, research, and product teams.

You may be a good fit if you:

• Have a track record of independently driving research projects from ambiguous problem statements to concrete results, ideally in AI, ML, security, integrity, or a related technical field.

• Are comfortable scoping your own work and switching between research, engineering, and analysis as a project demands.

• Have working familiarity with how large language models operate , sampling, prompting, training , even if LLMs aren't your primary background.

• Are proficient in Python and comfortable working with large datasets.

• Care about the societal impacts of AI and want your work to directly reduce real-world harm.

Strong candidates may also have:

• Experience building and training machine learning models, including classifiers for abuse, fraud, integrity, or security applications.

• Knowledge of evaluation methodologies for language models and experience designing evals.

• Experience with agentic environments and evaluating model behaviour in them.

• Background in trust and safety, integrity, fraud detection, threat intelligence, or adversarial ML.

• Experience with red teaming, jailbreak research, or interpretability methods like steering vectors.

• A history of taking research prototypes and transferring them into production systems.

Logistics

• Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience

• Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience

• Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position

Benefits

• Competitive compensation and benefits

• Optional equity donation matching

• Generous vacation and parental leave

• Flexible working hours

• Lovely office space in which to collaborate with colleagues

Visa Sponsorship

• We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

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This position follows the Company's hybrid schedule, which currently requires employees to work in the office at one of the following locations a minimum of three days per week: Addison, TX or Durham, NC.

Key Responsibilities:

• Define program scope, objectives, success metrics, milestones, and delivery plans
• Lead and coordinate cross-functional programs consisting of multiple workstreams
• Establish and maintain program governance, cadence, and reporting
• Identify, manage, and mitigate risks, issues, and dependencies
• Drive alignment between strategy, execution, and outcomes
• Track progress and escalate issues as needed
• Prepare and deliver program updates for leadership
• Assist with various program tasks
• Document program plans and processes in SharePoint, Planner or other PM tools

We're looking for a self-motivated, detail-oriented individual with strong project management skills and the ability to multitask and prioritize in a fast-paced environment. The ideal candidate will have experience with cross-functional collaboration, tech savvy with strong data evaluation skills, and an understanding of and strong alignment with our core values.

The annual base salary range for this full-time position is $70,000 to $130,000. This range is an estimate for what Tanium will pay a new hire. The actual annual base salary offered may be adjusted based on a variety of factors, including but not limited to, location, education, skills, training, and experience.

In addition to an annual base salary, team members will receive equity awards and a generous benefits package consisting of medical, dental and vision plan, family planning benefits, health savings account, flexible spending account, transportation savings account, 401(k) retirement savings plan with company match, life, accident and disability coverage, business travel accident insurance, employee assistance programs, disability insurance, and other well-being benefits.

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Key responsibilities include:

• Scaling the decision-making process for tools for the tvScientific AI team, from our workflows to our training infrastructure to our Kubernetes deployments
• Improving the developer experience for the data science team
• Upgrading our observability tooling
• Serving as a technical lead and mentor to the team
• Making every deployment smooth as our infrastructure evolves

Requirements include:

• Deep understanding of Linux
• Excellent writing skills
• A systems-oriented mindset
• Experience in high-performance software (RTB, HFT, etc.)
• Software engineering experience + reliability (e.g. CI/CD) expertise
• Strong observability instincts
• Demonstrated ability to use AI to improve speed and quality in your day-to-day workflow for relevant outputs
• Strong track record of critical evaluation and verification of AI-assisted work (e.g., testing, source-checking, data validation, peer review)
• High integrity and ownership: you protect sensitive data, avoid over-reliance on AI, and remain accountable for final decisions and deliverables

Nice-to-haves include:

• Reverse-engineering experience
• Terraform, EKS, or MLOps experience
• Python, Scala, or Zig experience
• NixOS experience
• Adtech or CTV experience
• Experience deploying a distributed system across multiple clouds
• Experience in hard real-time low-latency

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This hire will be instrumental in signalling and forecasting accurate demand, planning inventory levels, and ensuring that Anduril supports its hardware requirements via Enterprise Resource Planning (ERP) software and other associated tools. The right person for this role has demonstrated ownership and experience solving complex operational challenges with creative solutions in a fast-paced, resource-limited environment.

Your responsibilities will include managing day-to-day demand signalling, ordering, and inventory for various product lines, identifying and resolving supply issues by collaborating with Engineering, Purchasing, and Manufacturing teams, leading Sales and Operations Planning (S&OP) discussions for Supply Planning on designated product lines, working with Business Development and Growth teams to align forecasts with actual demand plans, reporting on and analysing supply and material health to inform key decisions for Engineering, Purchasing, Manufacturing, and Business Development, developing and maintaining processes within MRP systems and associated master data, and driving strategic initiatives towards best practices, including demand shaping, advanced modelling, and inventory optimisation.

To be successful in this role, you will need a Bachelor's degree in a technical field or business field, and 6+ years of experience in a supply chain or production role within a fast-paced manufacturing environment with complex mechanical and/or electrical assemblies. You will also need technical expertise, including the ability to read technical documentation and understand hardware manufacturing processes, experience with ERP systems such as Oracle, Netsuite, and CRM systems like Salesforce, and the ability to travel up to 10% of the time.

The salary range for this role is $129,000-$171,000 USD, and highly competitive equity grants are included in the majority of full-time offers. Additionally, Anduril offers top-tier benefits for full-time employees, including comprehensive medical, dental, and vision plans, income protection, generous time off, caregiver and wellness leave, family planning and parenting support, mental health resources, professional development, commuter benefits, relocation assistance, and a retirement savings plan.

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Responsibilities:

• Lead sourcing and outreach efforts for technical roles, leveraging various tools and social platforms.
• Screen and evaluate candidate qualifications, technical skills, and cultural alignment.
• Coordinate and facilitate interview processes, ensuring a positive and efficient experience for both candidates and interviewers.
• Provide regular updates and insights to hiring managers and stakeholders on pipeline health and recruiting progress.
• Maintain accurate and up-to-date candidate data in recruiting systems and dashboards.
• Contribute to continuous improvement of recruiting processes, tools, and candidate experience.
• Partner directly with Hiring Managers to drive hiring initiatives critical to building Brex's Engineering team.

Requirements:

• Proven experience recruiting for technical roles (e.g., software engineering, data, product) in a fast-paced, high-growth environment.
• Strong sourcing skills and familiarity with modern recruiting tools and platforms.
• Excellent communication, relationship-building, and stakeholder management abilities.
• Data-driven mindset with the ability to interpret recruiting metrics and make process improvements.
• Commitment to diversity, equity, and inclusion in all aspects of recruiting.
• Ability to manage multiple searches and priorities simultaneously.

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You'll need to know accelerator performance well to turn it into tasks and signals models can learn from. Specifically, you will:

• Invent, design and implement RL environments and evaluations.
• Conduct experiments and shape our research roadmap.
• Deliver your work into training runs.
• Collaborate with other researchers, engineers, and performance engineering specialists across and outside Anthropic.

We're looking for someone with expertise in accelerators (CUDA, ROCm, Triton, Pallas), ML framework programming (JAX or PyTorch), and experience with balancing research exploration with engineering implementation.

Strong candidates may also have experience with reinforcement learning, porting ML workloads between different types of accelerators, and familiarity with LLM training methodologies.

The annual compensation range for this role is $350,000-$850,000 USD.

Please note that we're an extremely collaborative group, and we value communication skills. The easiest way to understand our research directions is to read our recent research.

We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.

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Your work will focus on curating and annotating high-quality audio data to enhance Grok's global accessibility, enabling natural spoken interactions for users worldwide, bridging language barriers through accurate speech processing, and improving the AI's handling of multilingual audio nuances.

Responsibilities:

• Use proprietary software to provide labels, annotations, recordings, and inputs on projects involving multilingual audio clips, voice recordings, speech samples, and auditory elements in various languages.

• Support the delivery of high-quality curated audio data that ensures clear, natural spoken output, accurate representation of linguistic and prosodic details (such as intonation, rhythm, and accent), and professional audio standards.

• Collaborate with technical staff to develop tasks that improve AI's ability to handle speech modulation, accent variation, noise in real-world recordings, and multilingual audio processing.

• Work with technical staff to improve annotation tools for efficient audio workflows.

Basic Qualifications:

• Native proficiency in Polish with exposure to diverse accents, dialects, or regional variations.

• Proficiency in English (minimum B2 level) with clear, natural vocal delivery and pronunciation suitable for audio recording purposes.

• Strong auditory perception to identify nuances in speech, accents, pronunciation, intonation, and audio quality across languages.

• Demonstrated ability to handle multilingual audio content, including evaluating speech accuracy, cultural vocal expressions, and contextual interpretation in spoken form.

• Demonstrated ability to transcribe audio with high accuracy across accents and varying audio quality.

• Comfort providing high-quality voice recordings and feedback on audio samples in multiple languages.

• Strong comprehension skills and the ability to make independent judgments on ambiguous or varied audio material, including noisy or accented speech.

• Strong communication, interpersonal, analytical, detail-oriented, and organizational skills, with the ability to articulate audio-related feedback effectively.

• Commitment to developing AI that masters sophisticated multilingual audio capabilities.

Preferred Skills and Experience:

• Demonstration of exceptional attention to linguistic nuance, auditory detail, and data quality beyond standard transcription work.

• Deep understanding and taste of what good/useful Audio data is.

• Strong command of advanced transcription and annotation practices, including handling disfluencies, accents, and prosodic features (intonation, stress, rhythm, emotion, etc) with high consistency and accuracy.

• Background in linguistics (e.g., phonetics, phonology, sociolinguistics), speech sciences, cognitive science, or a related field, or equivalent practical experience, with demonstrated ability to analyze accent variation, pronunciation differences, and multilingual speech patterns.

• Experience working with speech/audio datasets, annotation workflows, or AI training data, including knowledge/experience with training voice models, and an understanding of how data quality impacts model performance.

• Professional experience in voice work, including voice acting, voice recording, podcasting with a measurable audience (e.g., X following), or similar audio production demonstrating attention to clarity and recording quality.

• Demonstrated ability to exercise independent judgment in ambiguous audio scenarios and make consistent, defensible annotation decisions.

• Portfolio (strongly preferred for advanced candidates): Voice samples, annotated transcripts, or audio-related work demonstrating quality, methodology, and attention to detail.

• Candidates with professional experience in voice, linguistics, speech data, or speech evaluation and research are especially encouraged to apply.

Location and Other Expectations:

• Tutor roles may be offered as full-time, part-time, or contractor positions, depending on role needs and candidate fit.

• For contractor positions, hours will vary widely based on project scope and contractor availability, with no fixed commitments required. On average, most projects may require at least 10 hours per week to deliver effectively, though this is not a fixed commitment and depends on the scope of work. Contractors have full flexibility to set their own hours and determine the exact amount of time needed to complete deliverables.

• Tutor roles may be performed remotely from any location worldwide, subject to legal eligibility, time-zone compatibility, and role-specific needs.

• For US-based candidates, please note that we are unable to hire in Wyoming and Illinois at this time.

• We are unable to provide visa sponsorship.

• For those who will be working from a personal device, your computer must be a Chromebook, a Mac with macOS 11.0 or later, or Windows 10 or later.

Compensation and Benefits:

US-based candidates: $35/hour - $45/hour depending on factors including relevant experience, skills, education, geographic location, and qualifications. International candidates: Information will be provided to you during the recruitment process.

Benefits vary based on employment type, location, and jurisdiction. Benefits for eligible U.S.-based positions include health insurance, 401(k) plan, and paid sick leave. Specific details and role-specific information will be provided to you during the interview process.

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The right person for this role has demonstrated ownership and experience solving complex operational challenges with creative solutions in a fast-paced, resource-limited environment. This person will be flexible to provide support wherever needed to ensure products are built and shipped under stringent quality standards.

Responsibilities:

Manage day-to-day demand signalling, ordering, and inventory for various product lines.

Identify and resolve supply issues by collaborating with Engineering, Purchasing, and Manufacturing teams.

Lead Sales and Operations Planning (S&OP) discussions for Supply Planning on designated product lines.

Work with Business Development and Growth teams to align forecasts with actual demand plans.

Report on and analyse supply and material health to inform key decisions for Engineering, Purchasing, Manufacturing, and Business Development.

Develop and maintain processes within MRP systems and associated master data.

Drive strategic initiatives towards best practices, including demand shaping, advanced modelling, and inventory optimisation.

Required Qualifications:

Bachelor's degree in a technical field (i.e. manufacturing, engineering, analytics, computer science, etc.) or business field (i.e. finance, economics, supply chain management, business administration, marketing, etc.).

6+ years of experience in a supply chain or production role within a fast-paced manufacturing environment with complex mechanical and/or electrical assemblies.

Complete ownership of a complex value chain, coordinating between multiple internal and internal parties to ensure on-time deliveries and adherence to quality standards.

Technical expertise including ability to read technical documentation and understanding hardware manufacturing processes.

Experience with ERP systems such as Oracle, Netsuite, and CRM systems like Salesforce.

Ability to travel up to 10% of the time.

Ability to relocate, if not already local to be onsite in Costa Mesa, CA.

Preferred Qualifications:

Master's degree or other higher education.

8+ years of experience in a supply chain or production role within a fast-paced manufacturing environment with complex mechanical and/or electrical assemblies.

Strong experience with SQL databases, including building custom queries for production and inventory metrics.

Proficiency in data analysis and reporting tools such as Tableau, Power BI, or Qlikview.

Knowledge of supply chain planning systems like Blue Yonder and best practices in demand planning, inventory management, and S&OP.

Experience with lean manufacturing, continuous improvement, six sigma principles, and big data evaluation techniques.

Proactive, able to take substantial responsibility across various functions, with a focus on speed and accuracy.

Ability to obtain and maintain a U.S. TS clearance.

Salary: The salary range for this role is $129,000-$171,000 USD.

Benefits:

Healthcare Benefits - US Roles: Comprehensive medical, dental, and vision plans at little to no cost to you.

UK & AUS Roles: We cover full cost of medical insurance premiums for you and your dependents.

IE Roles: We offer an annual contribution toward your private health insurance for you and your dependents.

Additional Benefits - Income Protection: Anduril covers life and disability insurance for all employees.

Generous time off: Highly competitive PTO plans with a holiday hiatus in December.

Caregiver & Wellness Leave is available to care for family members, bond with a new baby, or address your own medical needs.

Family Planning & Parenting Support: Coverage for fertility treatments (e.g., IVF, preservation), adoption, and gestational carriers, along with resources to support you and your partner from planning to parenting.

Mental Health Resources: Access free mental health resources 24/7, including therapy and life coaching.

Additional work-life services, such as legal and financial support, are also available.

Professional Development: Annual reimbursement for professional development - Commuter Benefits: Company-funded commuter benefits based on your region.

Relocation Assistance: Available depending on role eligibility.

Retirement Savings Plan - US Roles: Traditional 401(k), Roth, and after-tax (mega backdoor Roth) options.

UK & IE Roles: Pension plan with employer match.

AUS Roles: Superannuation plan.

Protecting Yourself from Recruitment Scams:

Anduril is committed to maintaining the integrity of our Talent acquisition process and the security of our candidates.

We've observed a rise in sophisticated phishing and fraudulent schemes where individuals impersonate Anduril representatives, luring job seekers with false interviews or job offers.

These scammers often attempt to extract payment or sensitive personal information.

To ensure your safety and help you navigate your job search with confidence, please keep the following critical points in mind:

No Financial Requests: Anduril will never solicit payment or demand personal financial details (such as banking information, credit card numbers, or social security numbers) at any stage of our hiring process.

Please always verify communications:

Direct from Anduril: If you receive an email from one of our recruiters, it will only come from an @anduril.com address.

Via Agency Partner: If contacted by a recruiting agency for an Anduril role, their email will clearly identify their agency.

If you suspect any suspicious activity, please verify the agency's authenticity by reaching out

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As a Machine Learning Engineer on the Support Experience team, you'll play a crucial role in enhancing our self-serve support experiences.

About the Team

The Support Experience engineering organization builds and improves Stripe's user support from end to end: how users get help within our products, how they get in touch with us when they have questions, and how our teams use internal tools to answer those questions.

Responsibilities

• Design and implement state-of-the-art ML models and large-scale ML systems for enhancing self-serve support capabilities, balancing ML principles, domain knowledge, and engineering constraints
• Develop and optimize contextual conversation models and ML-powered resolution flows for common support scenarios, using tools such as PyTorch, TensorFlow, and XGBoost
• Create and refine pipelines for training and evaluating models in both offline and online environments, with a focus on improving support quality and user satisfaction
• Implement ML features that streamline information collection and processing for support agents, enhancing overall support efficiency
• Collaborate with product, strategy, and content teams to propose, prioritize, and implement new AI-driven support features and improve answer capabilities

Requirements

• Bachelor's Degree in ML/AI or related field (e.g. math, physics, statistics)
• 3+ years in AI/ML and backend engineering, including building and operating production ML systems at global scale with stringent SLOs,balancing reliability, latency, and cost,with privacy, security, and compliance by design.
• Deep and up-to-date applied LLM experience: RAG/embeddings, tool use/function calling, agentic planning/orchestration architectures, post-training methods, code generation, benchmarks and evaluations, etc.
• Familiarity with classical ML methods and common frameworks e.g. Pytorch, TensorFlow.
• Proficient in Python; strong distributed systems and data science fundamentals.
• Experience working closely with product management, design, other engineers, and other cross-functional partners.
• Strong technical leadership and communication: mentoring and elevating engineers, elevating AI/ML awareness and posture within organizations, setting architectural direction, and driving alignment in ambiguity.

Preferred Qualifications

• MS/PhD degree in ML/AI or related field (e.g. math, physics, statistics)
• Experience working in Java or Ruby codebases
• Experience designing, deploying, and owning Agentic LLM solutions (e.g., multi-step orchestrators, tool use/function calling) specifically for complex customer support or internal workflow automation.
• Comfortable working with distributed teams across multiple locations and time zones

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We're looking for a Senior Technical Recruiter to join our team at Brex. As a Senior Technical Recruiter, you will be responsible for partnering with hiring managers and technical leaders to define team needs and role requirements, ensuring alignment on hiring goals.

This role involves sourcing, engaging, and assessing candidates through diverse channels, while managing the full recruitment cycle from outreach to onboarding. You will create strategies to attract and retain diverse technical talent, proactively building pipelines for present and future needs.

Additionally, you will track and analyze key hiring metrics to improve processes, collaborate with cross-functional teams to maintain fairness and efficiency, and champion Brex's employer brand by representing the company at events and on social platforms.

Responsibilities:

• Lead sourcing and outreach efforts for technical roles, leveraging various tools and social platforms.
• Screen and evaluate candidate qualifications, technical skills, and cultural alignment.
• Coordinate and facilitate interview processes, ensuring a positive and efficient experience for both candidates and interviewers.
• Provide regular updates and insights to hiring managers and stakeholders on pipeline health and recruiting progress.
• Maintain accurate and up-to-date candidate data in recruiting systems and dashboards.
• Contribute to continuous improvement of recruiting processes, tools, and candidate experience.
• Partner directly with Hiring Managers to drive hiring initiatives critical to building Brex's Engineering team.

Requirements:

• Proven experience recruiting for technical roles (e.g., software engineering, data, product) in a fast-paced, high-growth environment.
• Strong sourcing skills and familiarity with modern recruiting tools and platforms.
• Excellent communication, relationship-building, and stakeholder management abilities.
• Data-driven mindset with the ability to interpret recruiting metrics and make process improvements.
• Commitment to diversity, equity, and inclusion in all aspects of recruiting.
• Ability to manage multiple searches and priorities simultaneously.

Bonus points:

• Experience recruiting across multiple geographies (e.g., US, Canada, LATAM).
• Familiarity with compensation strategy and market analysis for technical roles.

Compensation: The expected salary range for this role is $142,380-$195,490. However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package.

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You'll guide organisations through their digital transformation journeys, from planning through monitoring, using your technical expertise, understanding of cloud and modern software development practices, and strong customer empathy.

Reporting to a regional Solutions Architect manager and partnering closely with Account Executives and cross-functional teams, you'll own technical evaluations (including proof of value initiatives and workshops), shape solution architectures, and serve as the voice of the customer back to Product Management.

In your first year, you'll focus on driving successful platform adoption, influencing revenue growth through solution selling, and building long-term, trust-based relationships that showcase GitLab's differentiated position in an AI-driven DevSecOps landscape.

Responsibilities:

• Lead technical discovery, demos, and validation (including proofs of value) to show how GitLab's AI-powered DevSecOps platform meets customers' technical and business needs across the full lifecycle.

• Drive the technical evaluation process as the Directly Responsible Individual, including solution design, POC/POV ownership, workshop design, and the technical components of tenders, audits, and value stream assessments.

• Collaborate with Account Executives and regional sales teams in Japan to shape and execute account strategies that support new customer acquisition and expansion.

• Build and deepen relationships with technical practitioners and business leaders, guiding them through GitLab-driven digital transformation and enabling them to become GitLab advocates.

• Advise customers on modern software development, continuous integration, continuous deployment, security, and cloud practices, challenging existing approaches to improve return on investment.

• Serve as the voice of the customer with Product Management, Engineering, Sales, and Marketing by sharing feedback, use cases, and competitive insights that inform roadmap and positioning.

• Maintain and extend your technical expertise in GitLab, DevSecOps, AI, and related cloud technologies, creating reusable examples, best practice guidance, and technical collateral for customers and partners.

• Invest in your own growth and development through ongoing learning, mentorship, and knowledge sharing to continuously improve the impact of the Solutions Architect team.

Requirements:

• Experience engaging with customers in technical pre-sales, consulting, or similar roles, guiding them through solution design and evaluation.

• Proficiency with the end-to-end software development lifecycle, including modern DevSecOps practices and continuous integration and continuous deployment workflows.

• Hands-on experience with GitLab or comparable source control, CI/CD, and collaboration platforms, and the ability to map platform capabilities to customer use cases.

• Practical knowledge of cloud computing concepts and related technologies, with the ability to discuss deployment, security, and operations options with technical teams.

• Ability to lead technical evaluations such as proofs of concept or proofs of value, contribute to tenders or audits, and design and run workshops or value stream assessments.

• Clear technical communication and presentation skills, with the ability to adapt messages for practitioners through to senior business and technical decision makers.

• Skill in building trusted relationships, listening with empathy, and acting as a customer advocate to internal teams such as Product, Engineering, Sales, and Marketing.

• Motivation to continuously develop professionally, including learning new technologies, deepening GitLab platform expertise, and applying transferable experience from related fields.

About the team:

We, the Solutions Architect team, are part of GitLab's Sales organization and serve as the technical counterpart to Account Executives, with this role focused on opportunities in Japan and reporting into a regional Solutions Architect Manager.

Our mission is to help customers realise the full value of GitLab's AI-powered DevSecOps platform by advising on architecture, running technical evaluations such as proofs of value, and guiding customers through their digital transformation.

We work closely with Sales, Product Management, Engineering, and Marketing, collaborating asynchronously across regions to share best practices, create reusable technical collateral, and act as the voice of the customer.

We are focused on helping customers modernise end-to-end software delivery, adopt GitLab at scale, and navigate a rapidly evolving AI and DevSecOps landscape.

How GitLab supports full-time employees:

• Benefits to support your health, finances, and well-being

• Flexible Paid Time Off

• Team Member Resource Groups

• Equity Compensation & Employee Stock Purchase Plan

• Growth and Development Fund

• Parental leave

• Home office support

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You'll lead deep technical engagements, partnering directly with startup engineering teams to help them develop their products on top of Claude,advising on implementation, agent design, and working alongside them to build at the frontier of AI.

Working closely with Applied AI Architects, Account Executives, and Anthropic's Product and Engineering teams, you'll guide startups through deep technical engagements. You'll leverage your AI engineering expertise to develop custom evaluation frameworks, design scalable architectures, and create the technical resources that enable startups to succeed with Claude.

Responsibilities:

• Serve as a deep technical advisor to high-potential startups, working alongside them to build innovative use cases that push the boundaries of AI

• Work hands-on with startup engineering teams: pair programming, architecture reviews, and code contributions that accelerate their development

• Develop prototypes and technical documentation,including evaluation suites, AI engineering techniques, and architecture diagrams,that enable startups to build and scale with Claude

• Collaborate closely with Applied AI Architects to maintain context and continuity across customer engagements

• Identify patterns across engagements and contribute insights back to Product, Engineering, and the broader Applied AI team

• Create technical content for startup audiences including documentation, tutorials, and sample code

• Foster community engagement through hackathons, webinars, technical office hours, and startup-focused events

• Travel to customer sites for workshops, implementation support, and relationship building

You may be a good fit if you have:

• 4+ years of experience as a Software Engineer, Forward Deployed Engineer, or technical founder

• Production experience building LLM-powered applications, including prompting, context engineering, agent architectures, evaluation frameworks, and deployment at scale

• Strong programming skills with proficiency in Python and experience building production applications

• Experience with startups or high-growth companies

• Ability to context-switch across industries (healthcare, fintech, etc.) and use cases

• Builder credibility that earns trust with technical founders and engineering teams,you've shipped products and can speak from experience

• Strong technical communication skills with the ability to translate complex AI concepts into architectural decisions and actionable implementation plans

• Experience facilitating technical workshops, hackathons, or developer-focused events

• Passion for making powerful technology safe and beneficial

The annual compensation range for this role is $200,000-$320,000 USD.

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The ideal candidate will have expertise in multimodality and experience running large-scale experiments. They will be comfortable contributing to complex engineering systems and have a strong grasp of probability, statistics, and machine learning fundamentals.

This is an evergreen role, meaning that the position is open on an ongoing basis. The company receives many applications, and there may not always be an immediate role that aligns perfectly with the candidate's experience and skills. However, they encourage candidates to apply and continuously review applications.

Responsibilities:

• Own research projects on training and performance analysis of multimodal AI models.
• Curate and build large-scale datasets and evaluation benchmarks to advance vision capabilities.
• Work with data infrastructure engineers, pretraining researchers and engineers, and product teams to create frontier multimodal models and the products that leverage them.
• Publish and present research that moves the entire community forward.

Skills and Qualifications:

• Ability to design, run, and analyze experiments thoughtfully, with demonstrated research judgment and empirical rigor.
• Understanding of machine learning fundamentals, large-scale training, and distributed compute environments.
• Proficiency in Python and familiarity with at least one deep learning framework (e.g., PyTorch, TensorFlow, or JAX).
• Comfortable with debugging distributed training and writing code that scales.
• Bachelor's degree or equivalent experience in Computer Science, Machine Learning, Physics, Mathematics, or a related discipline with strong theoretical and empirical grounding.

Preferred qualifications include research or engineering contributions in visual reasoning, spatial understanding, or multimodal architecture design, experience developing evaluation frameworks for multimodal tasks, publications or open-source contributions in vision-language modeling, video understanding, or multimodal AI, and a strong grasp of probability, statistics, and ML fundamentals.

Logistics:

• Location: San Francisco, California.
• Compensation: $350,000 - $475,000 USD per year, depending on background, skills, and experience.
• Visa sponsorship: Yes.
• Benefits: Generous health, dental, and vision benefits, unlimited PTO, paid parental leave, and relocation support as needed.

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You will work closely with Product, Marketing, and Pricing to bring real customer signals into decisions and help the company learn quickly what resonates, what converts, and what customers will pay for. This role often operates as a specialist overlay into existing Intercom customer accounts.

Key responsibilities include owning the full sales cycle for Sales Agent, running discovery with Sales, RevOps, and Marketing leaders, designing and managing structured evaluations, building and refining how we sell this product, and providing structured feedback to Product, Marketing, and Pricing.

The ideal candidate will have proven experience running full cycle SaaS sales processes from discovery through close, demonstrated ability to sell a new or evolving product, experience selling to sales leadership, RevOps, Marketing leadership, or adjacent GTM personas, and strong consultative selling and discovery skills.

Benefits include competitive salary and meaningful equity, comprehensive medical, dental, and vision coverage, regular compensation reviews, flexible paid time off policy, paid Parental Leave Program, 401k plan & match, in-office bicycle storage, fun events for Intercomrades, friends, and family, unlimited access to Claude Code and best-in-class AI tools, experimentation & building is encouraged & celebrated.

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The design space of biomolecules is unimaginably vast , far beyond what can be explored experimentally. Yet within this space lie molecules with properties essential for new medicines. Our machine learning models learn to design therapeutic biomolecules with specific, desirable functions.

We advance the state of the art in molecular design by training large-scale foundation models and developing cutting-edge generative approaches. The models learn from diverse heterogeneous datasets and are refined through focused fine-tuning and feedback from experiments. Key to progress is a team that combines exceptional machine learning expertise with thorough domain understanding.

You will collaborate closely with other machine learning researchers and engineers, as well as computational and experimental biologists, to advance these models and translate their capabilities into real therapeutic designs.

Responsibilities

• Embody our vision of an interdisciplinary environment and embrace learning about areas outside of your traditional area of expertise

• Develop, implement, train, and iteratively improve state-of-the-art models for biomolecule design

• Analyze, visualize, and communicate results to support team efforts in improving models and data

• Create, deploy, and refine tools for efficient, reliable machine learning experimentation and production

• Work with biologists to collect data for the training and evaluation of generative models of biomolecules

• Provide mentorship and technical direction to team members as appropriate

Qualifications

• 3+ years of hands-on experience developing ML models

• Demonstrated track record of implementing, training, improving advanced machine learning models

• Highly capable programmer fluent in Python ecosystem and PyTorch or similar deep learning framework

• Availability to work with team members across US and Europe, with meetings starting at 8am PT and ending at 7pm CET

• Readiness to travel several times a year for company retreats and business events

Compensation

$200K – $275K + Bonus + Equity

Benefits

• A competitive compensation package

• 30 days paid vacation per year

• Comprehensive health insurance for US based employees

• 401K with company match for US based employees and Direktversicherung for German employees

• Quarterly company-wide retreats

• Monthly wellness benefit

• Budget for multiple visits per year to our offices in Berlin, Palo Alto or Switzerland

• Learning & Development budget to attend conferences, take courses, or otherwise invest in your professional growth, as well as access to the Learning & Development platform EdX and Hone

• A buddy to help you get settled

At Inceptive, we are creating tools to develop increasingly powerful biological software for the rational design of novel, broadly accessible medicines and biotechnologies previously out of reach. Our team brings together vast expertise in molecular biology, machine learning, and software engineering, and we are all working towards becoming interdisciplinary, meaning we deepen the knowledge we have in our area of expertise while also expanding our knowledge of completely new fields.

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Working closely with our Sales, Product, and Engineering teams, you'll guide a focused portfolio of customers from technical discovery through successful deployment. You'll combine deep engineering expertise with customer-facing skills to help customers unlock the full potential of Claude APIs and move their products closer to the frontier, while maintaining our high standards for safety and reliability.

Responsibilities

• Serve as a specialist technical advisor to Anthropic customers as they deploy new products & workflows with our models: from discovery through deployment, coordinating internally across multiple teams to drive customer success

• Partner with account executives and solutions architects to translate customer business requirements into technical solutions

• Influence technical architecture decisions and customer product strategy by developing customized pilots, prototypes, and evaluation suites

• Lead hands-on technical workshops and code reviews with customer engineering teams

• Identify common design patterns and contribute insights back to our Product and Engineering teams

• Create scalable public and internal assets, documenting the latest LLM prompting, evaling, agentic, and architecture techniques

• Maintain strong knowledge of the latest developments in LLM capabilities, implementation patterns, and AI product development stacks

• Travel occasionally to customer sites for workshops, implementation support, and building relationships

• Attend conferences, lead speaking engagements, write blog posts and white papers on topics surrounding the AI space

Requirements

• 4+ years of experience in technical roles such as Forward Deployed Engineer, Software Engineer or Technical Product Manager with a desire to work closely with customers. Former technical founders are also encouraged to apply.

• Production experience with LLMs including advanced prompt engineering, agent development and frameworks, evaluation frameworks, transcript analysis, MCP, and deployment at scale

• Strong programming skills with proficiency in Python or TypeScript and experience building production applications

• Ability to navigate ambiguity and execute across domains with intellectual openness, finding simple solutions to complex problems

• High cooperation mindset for cross-organizational collaboration, balancing competing priorities with integrity

• Passion for advancing safe, beneficial AI systems through creative technical applications

• Exceptional communication skills to convey technical concepts to diverse stakeholders while maintaining a low ego and collaborative approach

Benefits

• Competitive compensation and benefits

• Optional equity donation matching

• Generous vacation and parental leave

• Flexible working hours

• Lovely office space in which to collaborate with colleagues

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The ideal candidate will have a strong background in supply chain or production, with experience in a fast-paced manufacturing environment dealing with complex assemblies. They will also have technical expertise, including the ability to read technical documentation and understand hardware manufacturing processes. Additional preferred qualifications include experience with ERP systems, SQL databases, and data analysis and reporting tools.

This is a full-time role that requires the ability to travel up to 10% of the time. The salary range for this role is $98,000-$130,000 USD, and highly competitive equity grants are included in the majority of full-time offers.

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Location: Victorville, California, United States

Job Description:

Anduril Industries is a defense technology company with a mission to transform U.S. and allied military capabilities with advanced technology. By bringing the expertise, technology, and business model of the 21st century's most innovative companies to the defense industry, Anduril is changing how military systems are designed, built and sold.

As the world enters an era of strategic competition, Anduril is committed to bringing cutting-edge autonomy, AI, computer vision, sensor fusion, and networking technology to the military in months, not years.

This position will be filled by a highly motivated Flight Test Avionics Technician with a passion for developmental flight test of a new and revolutionary products contributing valued mechanical expertise in all fields of aircraft maintenance.

You will work heavily with the program leadership and a wide spectrum of cross-departments to help build a team focused on solving hard problems and changing the industry forever.

The role will be responsible for aircraft mechanical assessment, maintenance coordination, flight execution, and reporting on all facets of aircraft readiness to the test program.

The Test and Evaluation team at Anduril works across the entire spectrum of products and business lines, as well as all flight operations and test range management.

Our team conducts full system level development testing, new production acceptance testing, sub-component qualification testing and much more.

In short, if it involves test, we support it.

If you are interested in working in an extremely innovative and fast-paced environment, where your work directly makes an impact and difference in the products that are fielded, this is a fantastic opportunity.

Responsibilities:

Service, troubleshoot, repair, inspect, and maintain aircraft avionics and ground support equipment in support of test operations and sustainment activities in accordance with maintenance documentation.

Modify, install, and test electronics and mechanical equipment as part of customer and company modification and test efforts.

Correct major and minor discrepancies by removal, repair, or replacement of defective avionics, electrical, payloads and subsystems.

Perform scheduled maintenance and functional checks on aircraft avionics, electrical, and subsystems.

Ability to fabricate, upgrade and modify aircraft harnesses, coax cables and fiber optic as well as install and checkout with limited engineering guidance.

Load and maintain software configuration on Aircraft and Ground Segment.

Extensive experience with software loads and regressions in a development environment.

Upkeep of DTED, WX, Aeronautical Charts, and other supporting information for GCS mission planning systems.

Troubleshoot, repair, and maintain aircraft and subsystems including landing gear, fuel system, flight control, and propulsion.

Conduct a variety of aircraft ground operations including Launch, Recovery, and Ground Engine run-up.

Perform standard preflight maintenance on prototype and experimental aircraft.

Complete aircraft and equipment documentation.

Communicate avionics assessment with engineering and manufacturing personnel.

Perform proper FOD and tool control practices.

Required Qualifications:

Excellent communication and teamwork abilities.

Proficient with computer use (standard browser, word processing applications).

Extensive experience and training in Install, troubleshooting and checkout of flight test instrumentation systems to include but not limited to strain gauges, accelerometers, string pots and all associated wiring.

Capable to perform tasks independently, manage time effectively, and make decisions without constant supervision or guidance.

Ability to meticulously interpret and work from engineering drawings and draft procedures, ensuring accuracy in translating technical specifications into practical applications.

Willing to be multi-capable. Which shall include some mechanical troubleshooting and repair.

Active TS Clearance, investigation within 5 years or continuous evaluation.

8 years or more of aircraft avionics experience.

5 years or more of developmental flight test experience.

Ability to rapidly change roles/responsibilities while working in a fast-paced, challenging work environment.

Ability to travel as required.

Preferred Qualifications:

5 years or more Test and Evaluation experience.

Valid FCC license.

ICP-A 620 certification.

US Hourly Range $47-$55 USD

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Key responsibilities include:

• Driving high-impact scientific work across GenAI-powered labeling and evaluation systems
• Identifying opportunities where LLMs and related methods can improve quality, speed, coverage, and cost efficiency
• Developing prototypes that demonstrate value in areas such as prompt optimization, task decomposition, quality estimation, routing, and human-in-the-loop workflows
• Designing rigorous measurement frameworks to evaluate model performance, workflow outcomes, and operational tradeoffs
• Partnering with engineering, product, and data science teams to shape roadmaps and productionize successful approaches
• Establishing strong standards for trustworthiness, including bias measurement, calibration, quality control, and responsible oversight
• Creating reusable methods and frameworks that can scale across teams and use cases

Requirements include:

• 10+ years of combined post-graduate academic and industry experience applying scientific methods to solve real-world problems on large-scale data
• Deep hands-on experience as an individual contributor solving technically complex, high-impact data science or ML problems
• Strong experience applying LLMs or other generative AI techniques to practical workflows, systems, or products
• Demonstrated ability to turn ambiguous problems into rigorous analyses, experiments, prototypes, and scalable solutions
• Proven track record of writing high-quality code and using technical work to influence product or platform direction
• Strong cross-functional collaboration skills and a track record of influencing leaders and peers through data and technical judgment
• Strong business and product sense with the ability to define meaningful success metrics and prioritize high-value opportunities
• Self-directed learning mindset and comfort working in a rapidly evolving technical landscape
• Experience with labeling systems, evaluation frameworks, human judgment workflows, or internal AI tooling is strongly preferred

In-office requirement statement: This role will need to be in the office for in-person collaboration 1-2 times/quarter and therefore can be situated anywhere in the country.

Relocation statement: This position is not eligible for relocation assistance.

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The team develops and enhances various AI models, ML services and tools including LLM fine-tuning and optimization, RAG/Search, LLM evaluation and testing automation, feedback-based learning and guardrail for a wide range of applications in Airbnb.

You will build and leverage cutting edge AI technologies to transform Airbnb’s customer service by delivering personalized, easy-to-use and proactive customer service experience.

A typical day involves envisioning, championing, and supporting the development of novel ML systems, product integrations, and performance optimizations to solve real-world problems.

Your expertise should include a PhD/Master’s degree, preferably in CS, or equivalent experience, and 5-12 years of ML engineering experience, with ownership responsibility over large-scale software systems.

Experience with LLM driven chatbot and Agentic AI products would be a big plus.

Excellent communication skills and the ability to work well within a team and with teams across the engineering, product & design organizations are also required.

Fluency in both English and Mandarin is essential.

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Key responsibilities include:

• Developing and deploying ML-based search and discovery relevance models and systems integrated with Databricks' products and services.
• Designing and implementing automated ML and NLP pipelines for data preprocessing, query understanding and rewrite, ranking and retrieval, and model evaluation, enabling rapid experimentation and iteration.
• Collaborating with product managers and cross-functional teams to drive technology-first initiatives that enable novel business strategies and product roadmaps for the search and discovery experience.
• Contributing to building a robust framework for evaluating search ranking improvements - both offline and online.

Requirements include:

• A Bachelor's degree in Computer Science or a related field, with a Master's or PhD preferred.
• 5+ years of experience developing search relevance systems at scale in production or in high-impact research environments.
• Experience applying LLM to search relevance.
• Strong understanding of computer science fundamentals.
• Contributions to well-used open-source projects.

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You will influence data strategy, drive build-vs-buy evaluations, and meaningfully shift Komodo's AI-native infrastructure and culture. Your responsibilities will include:

• Helping design company-wide AI vision, standards, and reference architectures.
• Defining and building foundational AI platforms (e.g., internal agent frameworks, orchestration systems).
• Acting as a multiplier by mentoring teams, running workshops, and driving organizational knowledge sharing.
• Making high-level technical decisions, including evaluating major build-vs-buy choices for platforms and tooling.
• Shaping Komodo's data strategy from an AI perspective,requirements, quality, orientation, and long-term structure.
• Leading complex applied research initiatives that push Komodo into new AI capability frontiers.
• Ensuring Komodo's AI systems meet high bars for reliability, accountability, ethics, and transparency.

The ideal candidate will be a recognized expert in applied AI with demonstrated impact across multiple teams or organizational domains. They will have extensive experience architecting end-to-end AI systems, multi-agent architectures, and large-scale orchestration frameworks. They will also have strong fluency in Python, GenAI frameworks (vLLM, Strands, Crew AI), and full-stack system integration.

We offer a competitive salary range of $274,000-$322,000 USD per year, depending on location. This role may be eligible for performance-based bonuses and equity awards. We also offer comprehensive health, dental, and vision insurance, flexible time off and holidays, 401(k) with company match, disability insurance and life insurance, and leaves of absence in accordance with applicable state and local laws and regulations and company policy.

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The impact you'll have:

• Create novel, never-seen-before interfaces for GenAI agents that manage complex workflows while keeping the human in the loop through inspectability and transparency
• Partner closely with product management, design, and other engineering teams to build intuitive, scalable, and extensible solutions that drive user & business growth
• Lead by example with hands-on full-stack software development to create dynamic, user-centric experiences
• Enable mechanisms that can drive product-led growth, through seamless onboarding and sharing capabilities
• Direct the future of intuitive agentic applications at Databricks, in collaboration with cross-functional teams of innovative software engineers, product managers, and designers
• Drive the strategy for building end-to-end AI feature development by designing, building, and maintaining systems that are scalable, reliable, and performant.

What we look for:

• 5+ years of experience with HTML, CSS, and JavaScript
• Demonstrated product mindset with the ability to translate ambiguous customer problems into scrappy MVPs and iterate quickly based on data and user feedback.
• You care that AI features feel intuitive, trustworthy, and helpful, not just bolted on to an existing app
• High ownership and bias for action in 0→1 environments: you are comfortable making pragmatic trade-offs, operating with incomplete information, and driving projects from idea through launch and adoption.
• Strong ability to collaborate across product, engineering, and design teams to align technical strategy with company growth objectives.
• Experience with modern JavaScript frameworks (e.g., React, Angular, or VueJs/Ember)
• 5+ years of experience with server-side web technologies (eg: Node.js, Java, Python, Scala, C#, C++,Go)
• Proven experience building and shipping end-to-end generative AI products
• Deep familiarity with LLMs and generative AI, including hands-on experience with techniques like retrieval-augmented generation (RAG), prompt design, evaluation, and monitoring AI quality and safety in production.

Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above.

Local Pay Range $166,000-$225,000 USD

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This role operates as a specialist overlay into existing Intercom customer accounts. You will work closely with Product, Marketing, and Pricing to bring real customer signals into decisions and help the company learn quickly what resonates, what converts, and what customers will pay for.

Key responsibilities include:

• Owning the full sales cycle for Sales Agent, from first conversation through evaluation, executive alignment, and close
• Running discovery with Sales, RevOps, and Marketing leaders to understand their inbound motion, define success, and quantify impact
• Designing and managing structured evaluations with your Solutions Engineer partner to prove measurable outcomes and create conviction
• Building and refining how we sell this product, including messaging, objection handling, competitive narratives, evaluation frameworks, and ROI proof points
• Partnering with core Relationship Managers to identify high-fit accounts, coordinate outreach, and keep account engagement disciplined and low-friction
• Providing structured feedback to Product, Marketing, and Pricing based on patterns across deals, including feature gaps, objections, and willingness to pay signals
• Helping define and improve sales process and operating cadence as we learn, including what we measure and what constitutes a qualified opportunity

Requirements:

• Proven experience running full cycle SaaS sales processes from discovery through close
• Demonstrated ability to sell a new or evolving product where positioning, ROI narrative, and evaluation plan are still being refined
• Experience selling to sales leadership, RevOps, Marketing leadership, or adjacent GTM personas
• Strong consultative selling and discovery skills with the ability to quantify value and align multiple stakeholders
• Comfort running structured evaluations and coordinating technical and commercial workstreams with Solutions Engineers and cross-functional partners
• Ability to synthesize customer feedback into clear product insights and messaging recommendations
• High ownership and adaptability in fast-moving environments

Bonus skills and attributes:

• Experience selling within sales tech or martech ecosystems
• Experience in a startup, scale-up, or new product line environment where you contributed to early go-to-market learning
• Familiarity selling AI-enabled products or automation tools
• Experience operating in an overlay or specialist model alongside account owners

Benefits:

• Competitive salary and equity in a fast-growing start-up
• We serve lunch every weekday, plus a variety of snack foods and a fully stocked kitchen
• Regular compensation reviews - we reward great work!
• Pension scheme & match up to 4%
• Peace of mind with life assurance, as well as comprehensive health and dental insurance for you and your dependents
• Flexible paid time off policy
• Paid maternity leave, as well as 6 weeks paternity leave for fathers, to let you spend valuable time with your loved ones
• If you’re cycling, we’ve got you covered on the Cycle-to-Work Scheme. With secure bike storage too
• MacBooks are our standard, but we also offer Windows for certain roles when needed

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Responsibilities:

• Develop the foundational systems which power Safeguards, including infrastructure for data storage and management, metric and evaluation systems, and tooling for human and agentic review.
• Ensure the day-to-day running of Safeguards systems and hold a high operational bar which serves both safety and customers while reducing the amount of human intervention and oversight required.
• Build robust and reliable multi-layered defenses for real-time improvement of safety mechanisms that work at scale

You may be a good fit if you have:

• Bachelor’s degree in Computer Science, Software Engineering or comparable experience
• 4-10+ years of experience in a software engineering position
• Proficiency in Python
• Ability to work across the stack
• Strong communication skills and ability to explain complex technical concepts to non-technical stakeholders

Strong candidates may also:

• Have experience building trust and safety, anti-spam, fraud or abuse detection and mitigation mechanisms and interventions for AI/ML systems
• Have experience building metrics and measurement systems or data and privacy management systems
• Have worked closely with operational teams to build custom internal tooling
• Be proficient in TypeScript or Rust
• Have experience with Claude Code or similar agentic coding tools

The annual compensation range for this role is £255,000-£325,000 GBP.

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More than 70,000 companies around the globe, including WeWork, Asana, NASDAQ, AAA Insurance, COMPASS Realty, Uber, Randstad, and Tractor Supply, rely on Dialpad to build stronger customer connections using real-time, AI-driven insights.

We’re now leading the shift to Agentic AI: intelligent agents that don’t just analyse conversations but take action by automating workflows, resolving customer issues, and accelerating revenue in real time. Our DAART initiative (Dialpad Agentic AI in Real Time) is redefining what a communications platform can do.

Visit dialpad.com to learn more.

Being a Dialer --------------- AI isn’t just a feature; it’s how our teams do their best work every day. We put powerful AI tools in every employee’s hands so they can move faster, think bigger, and achieve more.

We believe every conversation matters. And we’ve built the platform that turns those conversations into insight and action, for our customers and ourselves.

We look for people who are intensely curious and hold themselves to a high bar. Our ambition is significant, and achieving it requires a team that operates at the highest level.

We seek individuals who embody our core traits: Scrappy, Curious, Optimistic, Persistent, and Empathetic.

Your role -------- As a Sr. SDET in Agentic QA, you will own the test automation and quality frameworks that support Dialpad’s AI Voice Agent services.

You will develop automated tests for end-to-end product experiences, from frontend UI to backend services to APIs to audio/text interactions.

You will test orchestration flows, agent configuration experiences, and guardian safeguards to create robust automated coverage for functionality, performance, reliability, UX, and more.

In this role, you will develop substantial amounts of automated test infrastructure and partner deeply with the development team to make our fast-growing AI platform more testable, more stable, and more delightful for customers.

This position is based at one of Dialpad’s Canadian offices and reports to a QA Eng Manager in the United States.

What you’ll do ------------

• Own end-to-end quality for agentic features and workflows, including strategy, development, execution, and release qualification.
• Design and build automation tooling and frameworks for AI/LLM-driven systems, including prompt flows, agent orchestration, and tool integrations.
• Develop and maintain evaluation frameworks (evals) to measure response quality, accuracy, and hallucination rates.
• Drive automation coverage (80%+ for critical AI workflows) using deterministic + probabilistic validation approaches.
• Integrate AI quality checks into CI/CD pipelines with fast feedback cycles (
• Build tooling for LLM observability and debugging, including prompt tracing and response analysis.
• Partner with Applied AI teams on prompt engineering, model selection, and evaluation strategies.
• Design and execute performance and load tests for AI services (latency, throughput, cost efficiency).
• Identify and mitigate risks related to hallucinations, bias, safety, and edge cases.
• Define and track AI quality KPIs (task success rates, precision/recall, latency, etc.).
• Participate in design and architecture reviews to ensure systems are testable, observable, and resilient.
• Mentor engineers and contribute to raising the bar on AI quality engineering practices.

What you’ll bring --------------

• 5+ years of experience in software engineering or SDET roles with an emphasis on software development.
• Strong programming skills in Python (preferred), Java, or JavaScript.
• Experience testing distributed, cloud-native SaaS systems and APIs.
• Demonstrated proficiency in coding with AI agents to accelerate development and improve code quality.
• Hands-on exposure to LLMs or AI/ML systems (e.g., OpenAI, Claude, Gemini, or similar platforms).
• Understanding of non-deterministic systems and probabilistic testing approaches.
• Experience building test frameworks and scalable automation systems.
• Familiarity with AI evaluation techniques (benchmarking, golden datasets, human-in-the-loop validation).
• Experience with CI/CD pipelines (e.g., Jenkins, GitHub Actions).
• Strong collaboration skills with the ability to work across distributed teams and time zones.
• Bachelor’s degree in Computer Science or equivalent practical experience.

Backend: Python, Go, Google Cloud Platform, Cloud Run / App Engine, Kubernetes, Datastore, Redis, ElasticSearch.

• Frontend: Vue3, React.
• AI Stack: LLM APIs, LiveKit, prompt orchestration frameworks, evaluation tooling.

For exceptional talent based in British Columbia, Canada the target base salary range for this position is $150,500-$175,250 CAD.

Why Join Dialpad ---------------

• Work at the center of the AI transformation in business communications.
• Build and ship agentic AI products that are redefining how companies operate.
• Join a team where AI amplifies every employee’s impact.
• Competitive salary, comprehensive benefits, and real opportunities for growth.

We believe in investing in our people. Dialpad offers competitive benefits and perks, cutting-edge AI tools, and a robust training program that help you reach your full potential.

We have designed our offices to be inclusive, offering a vibrant environment to cultivate collaboration and connection.

Our exceptional culture, repeatedly recognized as a Great Place to Work, ensures that every employee feels valued and empowered to contribute to our collective success.

Don’t meet every single requirement? If you’re excited about this role and possess the fundamental traits, drive, and strong ambition we seek, but your experience doesn’t meet every qualification, we encourage you to apply.

Dialpad is an equal-opportunity employer. We are dedicated to creating a community of inclusion and an environment free from discrimination or harassment.

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We are seeking a highly skilled and experienced Staff Software Engineer to join our Communication Products team. As a Staff Engineer, you will be responsible for leading the technical vision for ML-powered messaging features, architecting and delivering intelligent capabilities end-to-end, and partnering deeply with ML and product teams.

The Difference You Will Make:

As a Staff Engineer on the team, you will define and drive the technical strategy for integrating ML capabilities into Airbnb's messaging products, including smart replies, message classification, content moderation, translation, and conversational assistance. You will also own the full lifecycle of ML-powered features: from prototyping and experimentation through launch, monitoring, and iteration.

A Typical Day:

• Design, build, and operate the systems that serve ML models within the messaging stack, with a focus on latency, reliability, and scalability
• Write and review technical designs that solve large, open-ended problems at the intersection of ML and product engineering without clearly-known solutions
• Partner with ML, data science, and product teams to identify high-value opportunities, establish evaluation criteria, and close the gap between offline model performance and production impact
• Collaborate with other engineers and cross-functional partners across Messaging, Trust & Safety, Localization, and Platform organizations to align on long-term technical solutions
• Mentor, guide, advocate, and support the career growth of individual contributors
• Establish engineering standards for ML integration across the messaging surface, including feature flagging, A/B testing, observability, and graceful degradation

Your Expertise:

• 9+ years of relevant engineering hands-on work experience
• Bachelors, Masters, or PhD in CS or related field
• Demonstrated experience building and shipping ML-powered product features in production environments, including model serving, feature pipelines, online/offline evaluation, and monitoring
• Exceptional architecture abilities and experience with architectural patterns of large, high-scale applications
• Familiarity with NLP/NLU techniques and large language models, particularly as applied to messaging, conversational AI, or content understanding
• Shipped several large-scale projects with multiple dependencies across teams, specifically at the intersection of ML infrastructure and product engineering
• Technical leadership and strong communication skills with the ability to translate between ML research, product goals, and engineering execution
• Experience operating distributed, real-time systems at scale with high reliability requirements
• Experience with real-time messaging systems or event-driven architectures
• Familiarity with ML infrastructure at scale (e.g., feature stores, model registries, online inference platforms)
• Prior work on trust & safety, content moderation, or internationalization in a messaging context
• Experience with LLM-based product features, including prompt engineering, retrieval-augmented generation, or fine-tuning

How We'll Take Care of You:

Our job titles may span more than one career level. The actual base pay is dependent upon many factors, such as: training, transferable skills, work experience, business needs and market demands. The base pay range is subject to change and may be modified in the future. This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits.

Pay Range: $204,000-$255,000 USD

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Key responsibilities include:

• Ensuring the Revenue Accounting and Billing team accounts and reports for infrastructure-as-a-service, software, SaaS and other revenue correctly under ASC 606 and other standards in its 10-K and 10-Q filings
• Collaborating with senior members of numerous other business functions to adapt to future business changes such as acquisitions, new products and new go to market strategies
• Partnering with the FP&A team to ensure proper forecasting of the company's revenue
• Updating and evolving the Commercial Accounting Team's accounting policies and positions in collaboration with the Technical Revenue team
• Driving the Commercial Accounting Team's internal, continuous process improvement initiatives
• Fostering and improving partnership with the Technical Revenue team to ensure seamless and efficient exchange of information to achieve accurate reporting results
• Managing a growing team of 10+ team members
• Overseeing and guiding the process for integrating the revenue accounting and billing processes of acquired companies
• Proposing and seeing through to completion process improvements across the Order to Cash cycle
• Leading and developing the Revenue Accounting and Billing team
• Performing certain SOX internal controls and ensuring successful performance of controls within the Revenue Accounting and Billing team
• Working with external auditors to address and close audit issues in a timely manner

The ideal candidate will have 10+ years of experience in Revenue Accounting at high-growth tech companies, 6+ years within public companies, 4+ years of Big 4 audit experience, and strong knowledge of ASC 606 and 340, knowledge of ASC 842 a plus.

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In this role, you will own the quality of results for two distinct but deeply connected 'users': the AI Agent and the Human User. You will optimize the retrieval layer that allows Large Language Models (LLMs) to reason over data they weren't trained on, ensuring they have the 'ground truth' needed to synthesize accurate, high-stakes business actions. You will also improve the traditional search experience so employees can find assets and answers through intuitive, high-recall interfaces.

This is a challenging problem that requires balancing traditional keyword-based search with semantic vector search. You will fine-tune ranking models that satisfy both human readability and LLM-ready context. You will also connect the dots across structured SQL tables, unstructured docs, and real-time business metrics.

If you want to solve the hardest problems in data discovery and see your work power the decision-making of thousands of people, let's talk.

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Responsibilities: Assess model outputs for factual accuracy, logical coherence, fallacious reasoning, and hidden assumptions. Identify subtle ideological capture, statistical fallacies, and rhetorical sleights of hand. Write exemplary reasoning that models intellectual honesty, source evaluation, nuanced weighing of primary and secondary sources, and scoping of confidence. Construct adversarial examples and red-team prompts to expose remaining epistemic weaknesses. Contribute to the definition and scaling of constitutional principles for truth-seeking behavior.

Basic Qualifications: Published analytical work and academic training in a high-rigor field. Strong Forecasting track record (e.g., Metaculus, Good Judgment), rigorous analysis, or public updating on errors. Deep knowledge in at least three of: philosophy of science, cognitive psychology, statistics, logic, linguistics, history, economics, or related disciplines. Ability to steel-man opposing views and separate settled knowledge from speculation. Habitual reliance on primary sources and base rates.

Preferred Skills and Experience: Experience in intelligence analysis, investigative journalism, or academic peer review.

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As a Sr. Compensation Partner, you will drive Anduril's success by bringing your compensation expertise to our leadership team and helping us scale. You will utilize and combine your prior high growth company experience, quantitative rigor, business mindset, and communication skills to serve as a strategic advisor to our People Business Partners.

Key responsibilities include:

• Partner with Senior Leaders and People Business Partners to drive and ensure the success of Anduril's compensation programs for Manufacturing including Production, Supply Chain, and Engineering teams at Arsenal-1.
• Guide People Business Partners and leadership teams throughout annual and mid-year compensation planning cycles specific to our Arsenal-1 population.
• Design, implement, and manage comprehensive compensation programs, including salary structures, incentive plans, and equity compensation, aligned with organisational strategy and market trends.
• Lead job evaluation processes, conduct market pricing analyses, and ensure internal equity and external competitiveness across all job families and levels.
• Partner closely with leadership and HR teams to resolve complex compensation issues, support strategic decision-making, and drive the implementation of compensation initiatives across the organisation.

In addition to these responsibilities, you will also work closely with our People Operations team during our annual & midyear compensation cycles including implementation, budgets, UAT testing and spearhead data integrity.

You will lead change management and communications of compensation practices with managers, team members, and across the People Team.

You will build strong partnerships with the Production/Manufacturing Division Leads, People Business Partner, Talent, Payroll, Legal, Stock, Finance and Accounting teams as well as our 3rd party vendors.

You will work closely with and interrogate compensation data, to form data driven guidance to People Business Partners and Leaders.

You're a proactive motivated problem solver; offering to fill skill gaps and offer solutions; we'd rather tell you slow down than accelerate.

You enjoy working at a place where no one minds if you leave early one day to go to an appointment or run an errand, but you also don’t mind responding to Slacks in the evening while you’re watching Netflix.

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Key responsibilities include:

• Author detailed ASC 606 technical accounting memos analysing complex revenue recognition scenarios and providing accounting conclusions
• Evaluate and establish revenue recognition treatment for new product offerings, including performance obligation identification, SSP evaluation, and contract modification assessments
• Advise business stakeholders on revenue accounting implications of new go-to-market strategies, pricing models, and unique commercial arrangements
• Review revenue contracts and prepare technical accounting documentation, including ASC 606 checklists and position papers to ensure revenue recognition compliance
• Lead technical research initiatives on emerging revenue recognition issues and present authoritative findings to senior management
• Develop and maintain comprehensive revenue recognition policies, procedures, and technical guidance documentation
• Translate complex technical accounting requirements into actionable business guidance for non-accounting stakeholders
• Prepare for revenue-related month end close activities and flux analysis
• Build and maintain relationships with cross-functional stakeholders to drive effective collaboration
• Participate in and contribute to process improvement and system implementation projects

You may be a good fit if you have 7+ years of progressive accounting experience, with extensive expertise in ASC 606 implementation and complex revenue recognition scenarios.

Strong candidates may have a Bachelor's degree in Accounting or Finance, CPA certification, and experience with technical accounting advisory work, including revenue recognition consulting or implementation experience.

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Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organisations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence.

This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk.

Okta's Business Technology organisation builds secure and intelligent internal platforms that power our global workforce. Our AI & Automation team is delivering next-generation tools and experiences by integrating GenAI and intelligent automation into workflows across IT, HR, Finance, Sales, Marketing and Customer Support.

We focus on real-world applications: virtual agents, AI copilots, internal RAG services, and AI-augmented self-service portals , all with scale, governance, and user experience in mind.

The Opportunity

As a Senior Software Engineer, Applied AI, you'll play a key role in building user-facing and backend systems that leverage GenAI to improve internal experiences and operations. This role requires strong full-stack engineering skills, with an emphasis on both AI integration and building intuitive, performant UIs that make AI accessible and useful to our internal customers.

You'll work closely with software engineers, product managers, and designers to build secure, intelligent tools for employees across Okta.

What You'll Do

• Design and build end-to-end GenAI-powered applications, including web-based UIs, API services, and backend orchestration.

• Implement and integrate LLM-based experiences using frameworks like LangChain, LlamaIndex, and tools like OpenAI, Claude, or Gemini.

• Define, implement, and champion operational excellence standards (SLOs, observability, incident response frameworks) for all services deployed.

• Develop responsive, accessible, and modern frontend interfaces using frameworks like React or Vue , with a focus on usability, performance, and trust in AI outputs.

• Build and maintain a library of reusable frontend components and hooks that allow other business delivery teams to easily 'drop in' GenAI capabilities into their own applications.

• Build and maintain retrieval-augmented generation (RAG) pipelines with vector search and embedding strategies (e.g., Pinecone, FAISS, Qdrant).

• Collaborate with designers and product managers to rapidly iterate on UX patterns for AI-powered experiences (e.g., prompt inputs, citations, summaries).

• Ensure security, privacy, observability, and test coverage across the full stack.

• Contribute to architecture decisions, engineering standards, and best practices for AI/automation systems.

• Partner with platform and infrastructure teams to ensure services scale reliably across the org.

What You'll Bring

• 5–8 years of software engineering experience with full-stack development, including 2+ years of building AI/ML-driven applications.

• Strong Python development skills and 5+ years experience building cloud-based services using AWS, Docker, and RESTful APIs.

• 2+ years of experience in frontend technologies like React, TypeScript, or Vue, and comfort working on UI/UX for internal tools or enterprise applications.

• Hands-on experience with LLM integration, RAG pipelines, prompt engineering, or orchestration frameworks like LangChain or LlamaIndex.

• Strong background in distributed systems, APIs, microservices, container orchestration (ECS/EKS), and cloud platforms (AWS/GCP/Azure).

• Familiarity with secure coding, authentication/authorisation, and internal data governance best practices.

• Ability to collaborate across engineering, design, and product teams , with a strong sense of user empathy and technical ownership.

• Bonus: Exposure to design systems, AI evaluation tooling, or real-time application performance monitoring.

Why Join Okta

• Make AI Real: Design and build AI-powered apps used daily by Okta employees.

• Full-Stack Challenge: Tackle end-to-end problems , from LLM orchestration to intuitive UIs.

• Trusted Innovation: Join a team committed to security, ethics, and technical excellence in AI.

#LI-MK1

#LI-hybrid

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In this role, you will support end users by improving field failure discovery, mitigation, and resolution processes, conducting root cause analysis, deploying fixes, and managing incidents across the GCS fleet. This position requires a strong problem-solving mindset and hands-on expertise in debugging and resolving complex compute hardware and software issues.

Key responsibilities include:

• Sustain Anduril's GCS deployments by combining an understanding of our customers' missions with familiarity of our products and delivered capabilities
• Triage, diagnose and root cause product incidents, driving postmortem actions including providing status visibility through resolution
• Consistently assess and seek to improve the quality of the fleet's observability and health telemetry in partnership with multiple functions across the GCS team
• Collect, organize, and analyze system failure data to define trends, drive proactive sustainment processes, and support resource allocation
• Support Anduril's global customers through proactive communications and detail-oriented execution
• Support the evaluation and improvement of product capabilities, analyzing customer communication and feedback for capability requirements, product performance indicators, and desired functionality

Required qualifications include:

• 4+ year of technical support experience with a focus on final-tier customer concern support
• Experience supporting and/or performing incident driven workflows requiring analysis, triage, and prioritization
• Experience in on-call support operations and working in limited risk tolerance environments
• Ability to work non-standard hours and weekends as needed
• Ability to obtain and maintain a U.S. Secret Security clearance

Preferred qualifications include:

• BA or BS degree from accredited institution, STEM degree, preferably in computer science, software engineering, electrical engineering, information technology, or similar
• Experience supporting and/or operating compute-enabled communications systems, including electronic warfare domain experience, as a DOD employee, contractor, or end-user
• Experience with observability tooling such as DataDog, Grafana, and Victor Ops; exposure to software development tooling such as Git and Jira
• Applicable industry certifications (e.g. CompTIA Network+, CCNA, Linux+)
• Familiarity with and/or experience administrating NixOS systems
• Experience working as a system administrator
• Experience executing sustainment and reliability workflows for a defense-focused service or product
• DOD, Law Enforcement, or other Government agency experience preferred
• Demonstrated experience as a self-starter, able to find and resolve issues on your own
• Experience performing trend analysis to inform business decisions
• Strong aptitude for problem solving in unstructured situations at the interface of hardware, software, and networking
• Ability to drive challenging and vague technical problems to clarity and resolution
• Proven ability to master a technical system and support it in operational environments
• Must demonstrate an innate drive to be self-sufficient across the depth and breadth of a technical system
• Daily practice of excellence and rigor - you execute the 100th rep of a process with the same focus and care as the first five reps
• Confident with navigating ambiguity and crafting new ways of doing things
• Excellent written, visual, and verbal communication skills
• Active SECRET (or higher level) security clearance

US Salary Range: $113,000-$149,000 USD

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This role is unique in that it directly improves the safety, trust, and quality of real-world user experiences by advancing Airbnb's ability to understand, interpret and act on content at scale. You will help shape how the platform reasons about listings, profiles, messages and other user-generated content by building the next generation of Trust Content Understanding Models.

The ideal candidate is a motivated and talented 'full-stack' Data Scientist with strong applied ML intuition and a bias toward impact, who can own and drive forward challenging, high-visibility initiatives such as:

• Advance Airbnb's content integrity capabilities by building Natural Language Processing (NLP) and LLM-based models that understand intent, policy compliance, quality and risk across listings, profiles, and user communications

• Develop high-performing models for detecting problematic or misleading content, including text classification, semantic similarity, information extraction and generative model-based reasoning for policy interpretation and enforcement

• Design and optimize human-in-the-loop Machine Learning (ML) systems for content review, labeling, escalation and continuous model improvement

• Build systems to detect emerging content risks and abuse patterns across regions, cohorts and surfaces using statistical, ML and representation-learning approaches

• Design intelligent sampling and evaluation strategies to measure rare events, policy recall, false positives/negatives and model blind spots in large-scale content systems

A Typical Day:

• Artificial Intelligence / Machine Learning: Build and deploy production AI/ML systems for content integrity and trust content understanding, including feature engineering, model development and evaluation, thresholding, error analysis and end-to-end model lifecycle management. This includes working with NLP and LLM-based models in real production settings.

• Inference: Partner with inference data scientists to conduct rigorous quantitative analyses, applying working knowledge of causal inference to interpret results, assess impact, and identify gaps and opportunities to improve content quality and trust outcomes.

• Optimization: Develop frameworks to analyze tradeoffs between enforcement accuracy, user experience, operational cost and coverage, and propose strategies to optimize overall system effectiveness.

• Communication & Collaboration: Deliver robust research reports with effective data visualizations, clear storytelling and bullet-proof accuracy to drive forward impact in collaboration with cross-functional partners in product, engineering and operations

• Empowerment: Think strategically about how to scale and evolve Airbnb's content integrity defenses, helping define the long-term vision for the role of AI-driven content understanding across the Trust ecosystem.

Your Expertise:

• 5+ years of industry experience in a quantitative analysis role with a Master’s degree in a quantitative field (computer science, statistics etc.), or 2+ years of experience with a Ph.D.

• State-of-the-art knowledge of AI/ML models

• Hands-on experience building, evaluating, and deploying NLP and LLM-based solutions, including text classification, information extraction, semantic understanding or generative applications.

• Working knowledge of causal inference

• Skilled in statistical programming (Python or R) and database usage (SQL)

• Proven ability to communicate clearly and effectively to audiences of varying technical levels

• Ability to translate complex findings and results into compelling narratives that drive impact

• Excellent project management, communication, and collaboration skills

• Trust & Safety experience is a plus

Your Location:

This position is US - Remote Eligible. The role may include occasional work at an Airbnb office or attendance at offsites, as agreed to with your manager. While the position is Remote Eligible, you must live in a state where Airbnb, Inc. has a registered entity. Click here for the up-to-date list of excluded states. This list is continuously evolving, so please check back with us if the state you live in is on the exclusion list. If your position is employed by another Airbnb entity, your recruiter will inform you what states you are eligible to work from.

Our Commitment To Inclusion & Belonging:

Airbnb is committed to working with the broadest talent pool possible. We believe diverse ideas foster innovation and engagement, and allow us to attract creatively-led people, and to develop the best products, services and solutions. All qualified individuals are encouraged to apply. We strive to also provide a disability inclusive application and interview process. If you are a candidate with a disability and require reasonable accommodation in order to submit an application, please contact us at: reasonableaccommodations@airbnb.com. Please include your full name, the role you’re applying for and the accommodation necessary to assist you with the recruiting process. We ask that you only reach out to us if you are a candidate whose disability prevents you from being able to complete our online application.

How We'll Take Care of You:

Our job titles may span more than one career level. The actual base pay is dependent upon many factors, such as: training, transferable skills, work experience, business needs and market demands. The base pay range is subject to change and may be modified in the future. This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits.

Pay Range $177,000-$208,000 USD

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Your work will directly shape how our models understand and optimize for what humans actually want , enabling Claude to be more useful, more reliable, and better aligned with human values.

This role focuses on pushing the frontier of reward modeling for large language models. You'll develop novel architectures and training methodologies for RLHF, research new approaches to LLM-based evaluation and grading (including rubric-based methods), and investigate techniques to identify and mitigate reward hacking.

You'll collaborate closely with teams across Anthropic, including Finetuning, Alignment Science, and our broader research organization, to ensure your work translates into concrete improvements in both model capabilities and safety.

We're looking for someone who can drive ambitious research agendas while also shipping practical improvements to production systems. You'll have the opportunity to work on some of the most important open problems in AI alignment, with access to frontier models and significant computational resources.

Your work will directly advance the science of how we train AI systems to be both highly capable and safe.

Responsibilities:

• Lead research on novel reward model architectures and training approaches for RLHF

• Develop and evaluate LLM-based grading and evaluation methods, including rubric-driven approaches that improve consistency and interpretability

• Research techniques to detect, characterize, and mitigate reward hacking and specification gaming

• Design experiments to understand reward model generalization, robustness, and failure modes

• Collaborate with the Finetuning team to translate research insights into improvements for production training pipelines

• Contribute to research publications, blog posts, and internal documentation

• Mentor other researchers and help build institutional knowledge around reward modeling

You may be a good fit if you:

• Have a track record of research contributions in reward modeling, RLHF, or closely related areas of machine learning

• Have experience training and evaluating reward models for large language models

• Are comfortable designing and running large-scale experiments with significant computational resources

• Can work effectively across research and engineering, iterating quickly while maintaining scientific rigor

• Enjoy collaborative research and can communicate complex ideas clearly to diverse audiences

• Care deeply about building AI systems that are both highly capable and safe

Strong candidates may also:

• Have published research on reward modeling, preference learning, or RLHF

• Have experience with LLM-as-judge approaches, including calibration and reliability challenges

• Have worked on reward hacking, specification gaming, or related robustness problems

• Have experience with constitutional AI, debate, or other scalable oversight approaches

• Have contributed to production ML systems at scale

• Have familiarity with interpretability techniques as applied to understanding reward model behavior

The annual compensation range for this role is $350,000-$500,000 USD.

Logistics:

• Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience

• Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience

• Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position

Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work.

Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links,visit anthropic.com/careers directly for confirmed position openings.

How we're different:

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact , advancing our long-term goals of steerable, trustworthy AI , rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.

The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.

Come work with us!

Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.

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In this pivotal leadership role, you will define and implement the next generation of foundational data science solutions, leveraging expertise in statistics, econometrics, machine learning, and other quantitative methods to optimize Reddit's Ads marketplace.

As a thought leader, you will champion scientific rigor, causal inference, and economic modeling, while providing deep mentorship to the broader team.

Key responsibilities include:

• Defining the future of Ads Data Science and owning the design and long-term evolution of our core Ads Data Science solutions and infrastructure
• Identifying fundamental gaps and opportunities in our current systems and leading the strategic design and scientific roadmap for new solutions
• Taking end-to-end ownership of complex problem domains such as full funnel acceleration, advertiser lifetime value (LTV), and developing advanced predictive and causal frameworks
• Establishing scientific standards and defining best practices for large-scale statistical modeling, economic analysis, causal inference, offline model evaluation, and A/B experimentation

Requirements include:

• Demonstrated expertise in at least one of the following: ads marketplace understanding, auctioning/bidding, ads creative & format evaluation, measurement & experimentation at scale
• Master's or Ph.D. in Economics, Statistics, Computer Science, Operations Research, or a related quantitative discipline
• Advanced proficiency in statistical programming (Python or R) and SQL
• Experience with statistical analysis, economic modeling, foundational machine learning and/or optimization techniques
• Strong understanding of experimental design, causal inference, or A/B testing methodologies

Benefits include comprehensive healthcare benefits, income replacement programs, 401k with employer match, global benefit programs, family planning support, gender-affirming care, mental health & coaching benefits, flexible vacation & paid volunteer time off, and generous paid parental leave.

The base salary range for this position is $268,000-$365,100 USD.

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Contribute to the design, implementation, and maintenance of the LLM Gateway, focusing on features like unified API endpoints for internal/externally hosted LLM, rate/token limit management, and intelligent failover mechanisms to boost uptime and reliability.

Lead and execute the vision, strategy, and roadmap for Reddit's large-scale GenAI Platform.

Define the platform architecture and operating model that enable teams to build, deploy, and scale GenAI products reliably.

Drive the strategy for a unified LAG Gateway supporting internally and externally hosted LLMs through consistent APIs and abstractions.

Set the direction for core platform capabilities such as rate and token limit management, intelligent failover, and production resilience.

Shape Reddit's approach to an enterprise-grade RAG system.

Establish the strategic direction for agentic AI workflows and tool-use patterns across the platform.

Own the end-to-end platform strategy from concept through production adoption and long-term evolution.

Drive MLOps and LLMOps standards across CI/CD, testing, versioning, evaluation, and lifecycle management.

Define best practices for observability, monitoring, governance, and operational excellence across GenAI systems.

Partner across engineering, product, and leadership to align platform investments with company priorities and user needs.

Champion platform thinking with a strong focus on scalability, reliability, performance, and developer experience.

Influence technical direction across teams by turning emerging AI capabilities into a scalable platform strategy.

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The ideal candidate will have 5+ years of mechanical engineering experience in advanced air vehicle programs. They will be familiar with hypersonic missile systems and military standards. They will have hands-on experience integrating electrical and mechanical subsystems into high-speed air vehicles. They will be proficient in designing mechanical parts using CAD software and a strong understanding of manufacturing methods, including machining, sheet metal work, composites, 3D printing, injection molding, and composite lamination. They will have a strong understanding of mechanical engineering fundamentals and first principles. They will hold a BS or higher degree in Mechanical, Aerospace, or Electrical Engineering. They will be eligible to obtain and maintain an active U.S. Secret security clearance.

Preferred qualifications include experience using Siemens NX and Teamcenter software. Expertise in air vehicle subsystem layouts, architectural trade studies, and vendor data evaluations is also desirable. An active DoD Top Secret security clearance is preferred. Proficiency in advanced engineering analysis, including structural, thermal, and/or electrical domains, is also a plus.

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Your work will span the full lifecycle of model development. You'll research and build new long-horizon evaluations that test the boundaries of what our models can achieve, develop novel approaches to measuring emerging capabilities, and deepen our understanding of how those capabilities develop , both during production RL training and after. You'll also take a cross-organisational view, working across Reinforcement Learning, Pretraining, Inference, Product, Alignment, Safeguards, and other teams to map the landscape of model evaluations at Anthropic and identify critical gaps in coverage.

This role carries significant visibility and impact. You'll help shape the evaluation narrative for model releases, contributing directly to how Anthropic communicates about its models to both internal and external audiences. Done well, you will change how the industry measures and understands model capabilities, significantly furthering our safety mission.

Responsibilities:

• Build new novel and long-horizon evaluations
• Develop novel measurement approaches for understanding how model capabilities emerge and evolve during RL training
• Lead strategic evaluation coverage across the company
• Shape the evaluation narrative for model releases
• Lead and mentor a small team of researchers and research engineers, setting research direction and fostering a culture of rigorous, creative research
• Design evaluation frameworks that balance scientific rigor with the practical demands of production training schedules
• Build and maintain relationships across Anthropic's research organisation to ensure evaluation insights inform training and deployment decisions
• Contribute to the broader research community through publications, open-source contributions, or external engagement on evaluation best practices

You may be a good fit if you:

• Have significant experience designing and running evaluations for large language models or similar complex ML systems
• Have led technical projects or teams, either formally or through sustained ownership of critical research directions
• Are equally comfortable designing experiments and writing code,you can move between research and implementation fluidly
• Think strategically about what to measure and why, not just how to measure it
• Can synthesise information across multiple teams and workstreams to form a coherent picture of model capabilities
• Communicate complex technical findings clearly to both technical and non-technical audiences
• Are results-oriented and thrive in fast-paced environments where priorities shift based on research findings
• Care deeply about AI safety and want your work to directly influence how capable AI systems are developed and deployed

Strong candidates may also have:

• Experience building evaluations for long-horizon or agentic tasks
• Deep familiarity with Reinforcement Learning training dynamics and how model behaviour changes during training
• Published research in machine learning evaluation, benchmarking, or related areas
• Experience with safety evaluation frameworks and red teaming methodologies
• Background in psychometrics, experimental psychology, or other measurement-focused disciplines
• A track record of communicating evaluation results to inform high-stakes decisions about model development or deployment
• Experience managing or mentoring researchers and engineers

Representative projects:

• Designing and implementing a suite of long-horizon evaluations that test model capabilities on tasks requiring sustained reasoning, planning, and tool use over extended interactions
• Building systems to track capability development across RL training checkpoints, surfacing insights about when and how specific capabilities emerge
• Conducting a cross-org audit of evaluation coverage, identifying blind spots, and prioritising new evaluations to fill critical gaps across Pretraining, RL, Inference, and Product
• Developing the evaluation methodology and narrative for a major model release, working with research leads and communications to clearly characterise model capabilities and limitations
• Researching and prototyping novel evaluation approaches for capabilities that are difficult to measure with existing benchmarks
• Leading a team effort to build reusable evaluation infrastructure that serves multiple teams across the research organisation

The annual compensation range for this role is $850,000.

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In this role, you will set technical direction and lead execution for ML evaluation and the end-to-end data flywheel powering CSxAI products. Your work will define how we measure quality, how we turn feedback into learning signals, and how we continuously improve models and products safely and efficiently.

You will partner closely with product, engineering, design, and operations to build evaluation systems that are trusted, scalable, and actionable - connecting offline metrics to online outcomes.

A typical day in this role will involve working with large-scale structured and unstructured data, exploring, experimenting, building, and continuously improving Machine Learning models and pipelines for Airbnb product, business, and operational use cases.

You will work collaboratively with cross-functional partners, including product managers, operations, and data scientists, to identify opportunities for business impact, understand, refine, and prioritize requirements for machine learning, and drive engineering decisions.

Hands-on development, productionization, and operation of Machine Learning models and pipelines at scale, including both batch and real-time use cases, will also be a key part of this role.

You will leverage third-party and in-house Machine Learning tools and infrastructure to develop reusable, highly differentiating, and high-performing Machine Learning systems, enable fast model development, low-latency serving, and ease of model quality upkeep.

Your expertise will be critical in defining evaluation strategy and success metrics for GenAI systems, aligning offline evaluation with online business and customer experience outcomes.

You will build and scale evaluation frameworks with strong controls for bias, drift, and reliability, design the data flywheel, and lead cross-functional quality initiatives across product, ops, and engineering.

You will develop and productionize pipelines for dataset creation, model monitoring, evaluation-at-scale, and continuous testing, and drive technical decisions and architecture for evaluation and data infrastructure.

Minimum qualifications for this role include a PhD in Computer Science, Mathematics, Statistics, or a related technical field, industry experience of 10+ years building, testing, and shipping ML/AI systems end-to-end, and leadership experience of 5+ years leading large, ambiguous technical initiatives as a senior IC.

Preferred qualifications include customer support systems experience, infrastructure and quality at scale experience, agile practice for applied AI experience, and continuous learner experience.

This position is US-Remote Eligible, and the role may include occasional work at an Airbnb office or attendance at offsites, as agreed to with your manager.

Our job titles may span more than one career level, and the actual base pay is dependent upon many factors, such as training, transferable skills, work experience, business needs, and market demands.

The base pay range is $244,000-$305,000 USD, and this role may also be eligible for bonus, equity, benefits, and Employee Travel Credits.

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Our team is responsible for building systems that operate at internet scale and directly influence user experience, advertiser value, and business outcomes. You will work on high-impact systems that improve ranking, recommendations, search relevance, prediction, content/user understanding, and optimization systems.

As a Senior Machine Learning Engineer, you will:

• Design, build, and deploy production-grade machine learning models and systems at scale
• Own the full ML lifecycle: from problem definition and feature engineering to training, evaluation, deployment, and monitoring
• Build scalable data and model pipelines with strong reliability, observability, and automated retraining
• Work with large-scale datasets to improve ranking, recommendations, search relevance, prediction, content/user understanding, and optimization systems
• Partner cross-functionally with Product, Data Science, Infrastructure, and Engineering teams to translate complex problems into ML solutions
• Improve system performance across latency, throughput, and model quality metrics
• Research and apply state-of-the-art machine learning and AI techniques, including deep learning, graph & transformers based, and LLM evaluation/alignment

Basic Qualifications:

• 3-5+ years of experience building, deploying, and operating machine learning systems in production
• Strong programming skills in Python, Java, Go, or similar languages, with solid software engineering fundamentals
• ML Fundamentals: a strong grasp of algorithms, from classic statistical learning (XGBoost, Random Forests, regressions) to DL architectures (Transformers, CNNs, GNNs)
• Hands-on experience with modern ML frameworks (e.g., PyTorch, TensorFlow)
• Experience designing scalable ML pipelines, data processing systems, and model serving infrastructure
• Ability to work cross-functionally and translate ambiguous product or business problems into technical solutions
• Experience improving measurable metrics through applied machine learning

Preferred Qualifications:

• Experience with recommender systems, search/ranking systems, advertising/auction systems, large-scale representation learning, or multimodal embedding systems
• Familiarity with distributed systems and large-scale data processing (Spark, Kafka, Ray, Airflow, BigQuery, Redis, etc.)
• Experience working with real-time systems and low-latency production environments
• Background in feature engineering, model optimization, and production monitoring
• Experience with LLM/Gen AI techniques, including but not limited to LLM evaluation, alignment, fine-tuning, knowledge distillation, RAG/agentic systems and productionizing LLM-powered products at scale
• Advanced degree in Computer Science, Machine Learning, or related quantitative field

Potential Teams:

• Ads Measurement Modeling
• Ads Targeting and Retrieval
• Advertiser Optimization
• Ads Marketplace Quality
• Ads Creative Effectiveness
• Ads Foundational Representations
• Ads Content Understanding
• Ads Ranking
• Feed Relevance
• Search and Answers Relevance
• ML Understanding
• Notifications Relevance

Benefits:

• Comprehensive Healthcare Benefits and Income Replacement Programs
• 401k with Employer Match
• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave

Pay Transparency:

This job posting may span more than one career level. In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/. To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below. The base salary range for this position is $216,700-$303,400 USD

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Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organisations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence.

This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk.

Okta's Business Technology organisation builds secure and intelligent internal platforms that power our global workforce. Our AI & Automation team is delivering next-generation tools and experiences by integrating GenAI and intelligent automation into workflows across IT, HR, Finance, Sales, Marketing and Customer Support.

We focus on real-world applications: virtual agents, AI copilots, internal RAG services, and AI-augmented self-service portals , all with scale, governance, and user experience in mind.

The Opportunity

As a Senior Software Engineer, Applied AI, you'll play a key role in building user-facing and backend systems that leverage GenAI to improve internal experiences and operations. This role requires strong full-stack engineering skills, with an emphasis on both AI integration and building intuitive, performant UIs that make AI accessible and useful to our internal customers.

You'll work closely with software engineers, product managers, and designers to build secure, intelligent tools for employees across Okta.

What You'll Do

• Design and build end-to-end GenAI-powered applications, including web-based UIs, API services, and backend orchestration.

• Implement and integrate LLM-based experiences using frameworks like LangChain, LlamaIndex, and tools like OpenAI, Claude, or Gemini.

• Define, implement, and champion operational excellence standards (SLOs, observability, incident response frameworks) for all services deployed.

• Develop responsive, accessible, and modern frontend interfaces using frameworks like React or Vue , with a focus on usability, performance, and trust in AI outputs.

• Build and maintain a library of reusable frontend components and hooks that allow other business delivery teams to easily 'drop in' GenAI capabilities into their own applications.

• Build and maintain retrieval-augmented generation (RAG) pipelines with vector search and embedding strategies (e.g., Pinecone, FAISS, Qdrant).

• Collaborate with designers and product managers to rapidly iterate on UX patterns for AI-powered experiences (e.g., prompt inputs, citations, summaries).

• Ensure security, privacy, observability, and test coverage across the full stack.

• Contribute to architecture decisions, engineering standards, and best practices for AI/automation systems.

• Partner with platform and infrastructure teams to ensure services scale reliably across the org.

What You'll Bring

• 5–8 years of software engineering experience with full-stack development, including 2+ years of building AI/ML-driven applications.

• Strong Python development skills and 5+ years experience building cloud-based services using AWS, Docker, and RESTful APIs.

• 2+ years of experience in frontend technologies like React, TypeScript, or Vue, and comfort working on UI/UX for internal tools or enterprise applications.

• Hands-on experience with LLM integration, RAG pipelines, prompt engineering, or orchestration frameworks like LangChain or LlamaIndex.

• Strong background in distributed systems, APIs, microservices, container orchestration (ECS/EKS), and cloud platforms (AWS/GCP/Azure).

• Familiarity with secure coding, authentication/authorisation, and internal data governance best practices.

• Ability to collaborate across engineering, design, and product teams , with a strong sense of user empathy and technical ownership.

• Bonus: Exposure to design systems, AI evaluation tooling, or real-time application performance monitoring.

Why Join Okta

• Make AI Real: Design and build AI-powered apps used daily by Okta employees.

• Full-Stack Challenge: Tackle end-to-end problems , from LLM orchestration to intuitive UIs.

• Trusted Innovation: Join a team committed to security, ethics, and technical excellence in AI.

#LI-MK1

#LI-hybrid

P24739_3355024

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This is a high-leverage role. The tools you build will be used by dozens of researchers and investigators, and directly shape our ability to measure and mitigate both misuse and misalignment.

You'll work across the full stack, from core analysis frameworks through user-facing apps and interfaces.

Responsibilities:

• Design and implement AI-based monitoring systems for AI training and deployment
• Extend and improve core frameworks for processing large volumes of unstructured text
• Partner with researchers and safety teams across Anthropic to understand their analytical needs and build solutions
• Develop agentic integrations that allow AI systems to autonomously investigate and act on analytical findings
• Contribute to the strategic direction of the team, including decisions about what to build, what to partner on, and where to invest

You May Be a Good Fit If You:

• Have 5+ years of software engineering experience, with meaningful exposure to ML systems
• Are excited about the problem of scaling human oversight of AI systems
• Are familiar with LLM application development and evaluation
• Enjoy building tools that other people use , you care about UX, reliability, and documentation
• Thrive in collaborative, cross-functional environments

Strong Candidates May Also Have:

• Experience with productionizing internal tools or building developer-facing platforms
• Background in building monitoring or observability systems
• Comfort with ambiguity , our team is small and growing, and you'll help define what we become

The annual compensation range for this role is $320,000-$405,000 USD.

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Typical problems you will deal with include designing efficient and robust environments for AI agents, improving evaluations and observability, onboarding new evaluation datasets, standardizing preprocessing pipelines, and creating data augmentation pipelines.

Responsibilities include creating and maintaining frameworks for agent, data, and model evaluation tasks, building environments for AI agents, tools for automating common workflows, improving alerts, metrics, and error handling on large-scale RL jobs, refactoring existing frameworks for better modularity, and designing operation procedures and coding standards.

Basic qualifications include experience building and maintaining frameworks, building high-performance sandboxes, virtual machines, and simulations, building full-stack apps for automating workflows and data visualization, rapid iteration of research to production cycles, and test automation, CI/CD.

Base salary is $180,000 - $440,000 USD, and our total rewards package includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short & long-term disability insurance, life insurance, and various other discounts and perks.

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Our mission is to fundamentally improve our customers' quality of life by empowering organisations and the individuals that drive them to reimagine the way they operate, collaborate, and innovate in Airtable.

We sit at the confluence of Sales, Services, Product, and Marketing and take a customer-centric approach to creating value through intentful listening, storytelling, expert guidance, tailored solutions, and applying a highly consultative process.

Key responsibilities include:

• Collaborating with Pre-Sales teams to identify, qualify, and drive revenue opportunities at Enterprise accounts
• Building meaningful relationships with and serving as a trusted advisor to a prospect or customer's technical teams
• Owning the technical evaluation process, showcasing customer-centric value within the context of the customer's unique requirements, workflows, and business process needs
• Translating the value of Airtable's tooling into the language of the customer
• Managing multiple sales cycles simultaneously, proactively communicating with stakeholders and prioritising effectively
• Consulting with credibility, bringing a well-rounded and unique perspective with hands-on cross-functional experience
• Informing the product team and ultimately the product roadmap with meaningful market potential findings
• Representing Airtable in every engagement with the utmost care

Requirements include:

• 5+ years of experience in SaaS Pre-Sales
• 7+ years industry experience
• Experience managing sales cycles and owning the technical evaluation
• Working knowledge of Marketing, Product Operations, Retail Management, and other Business Units
• Knowledge of business operations, including understanding value drivers for various personas and industries
• Understanding best practices for structuring data in a relational database and database architecture
• Passionate about creating unique solutions for complex business problems
• Loves the spotlight, being an adaptable and compelling communicator and presenter
• Thirst for knowledge, being a researcher, analyst, and emerging trends enthusiast
• Technically savvy, demonstrating a deep understanding of enterprise integration methodologies, best practices, and API architecture
• Low-code, no-code application experience throughout the customer lifecycle
• Knowledge of complementary technologies and products, including data warehousing and AI systems

We value passion, creativity, autonomy, purposefulness, time management, and curiosity.

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With tools that amplify your impact and a culture that backs your ambition, you won't just contribute. You'll make things happen–fast.

The Opportunity:

ZoomInfo built the industry's most sophisticated GTM data acquisition infrastructure. Now we're applying that same rigor to context engineering,the emerging discipline that determines whether AI systems deliver transformative value or incremental improvement.

This role architects the context layer powering our AI intelligence across Copilot, GTM Studio, and MarketingOS. You'll transform how ZoomInfo's agentic workflows access, compress, and deliver precisely the right information at exactly the right moment.

The impact is organization-wide: every AI interaction, every intelligent recommendation, every autonomous agent action depends on the context infrastructure you’ll build.

We've transitioned to AI-first product thinking company-wide. The context pipelines exist but remain nascent,creating a rare opportunity to define architectural patterns and platform standards that compound value across multiple product teams in the years to come.

What You'll Do:

Architect Context Acquisition Pipelines

Design and optimize how ZoomInfo retrieves, transforms, and delivers context from our semantic data layer, memory systems, and data producers. You'll balance retrieval quality against latency and cost constraints, implementing hybrid search strategies, intelligent caching, and context compression techniques that maintain information density while respecting token budgets.

Own the Context Layer Platform

Build infrastructure serving multiple product teams,Copilot, GTM Studio, MarketingOS,as internal customers. Establish API contracts, developer experience standards, and integration patterns that accelerate feature velocity.

Maintain the delicate balance between providing flexible building blocks and opinionated solutions that encode best practices.

Drive Quality Through Measurement

Implement evaluation frameworks using RAGAS metrics and custom benchmarks. Monitor retrieval precision, context relevance, hallucination rates, and system performance in production.

Translate quality signals into architectural improvements, working closely with ML engineers to iterate on embedding models, reranking strategies, and retrieval algorithms.

Navigate Emerging Research

Context engineering evolves weekly. You'll continuously evaluate innovations,GraphRAG for multi-hop reasoning, test-time compute scaling, multimodal retrieval, compression techniques,determining which advances warrant production investment versus which remain academic curiosities.

Bring external best practices to ZoomInfo while contributing learnings back to the broader community.

Orchestrate Cross-Functional Execution

Translate between three distinct worlds: ML engineers optimizing retrieval algorithms, platform engineers building scalable infrastructure, and product teams shipping customer features.

Establish communication cadences, prioritization frameworks, and decision-making processes that balance urgent requests against strategic platform development.

What You’ll Bring:

• 4-6 years of product management experience with 2+ years in ML/AI infrastructure

• Direct experience with production RAG systems, vector databases, or semantic search, context management

• Experience with graph databases (e.g. Neo4j)

• Track record building platform products serving multiple internal or external customers

• Familiarity with context compression, embedding models, and retrieval evaluation frameworks

• History of defining product vision in nascent technical domains where best practices are still emerging

Who You Are:

Technical Foundation

Expert-level understanding of RAG system architecture,you can discuss embedding dimensionality trade-offs, vector database indexing strategies, and reranking approaches with depth.

You've built or significantly contributed to production retrieval systems, not just managed them at arm's length.

Python and SQL proficiency enables you to review code, analyze retrieval issues, and prototype solutions for concept validation.

Platform Product Mindset

Experience building infrastructure products where internal engineering teams are your customers.

You measure success through downstream product velocity improvements and developer satisfaction scores, not just uptime metrics.

You understand platform economics,how each additional team using your infrastructure increases its value through shared learnings and amortized costs.

Intellectual Velocity

You read recent research papers from arXiv, ACL, NeurIPS.

You prototype emerging techniques to understand their practical constraints.

You maintain strong opinions weakly held, updating your architectural assumptions as evidence accumulates.

The discipline moves too fast for static expertise,continuous learning is non-negotiable.

Strategic Communication

You translate between technical depth and business impact fluently.

You can explain to executives why implementing GraphRAG takes 6 months but unlocks $10M in product capabilities.

You can communicate to engineers why business constraints require shipping 'good enough' in 3 weeks rather than 'optimal' in 3 months.

You influence without formal authority through data, clear reasoning, and earned credibility.

The Environment:

Reporting & Collaboration

Report to the Senior Product Director for Context Engineering, Semantic Data Layer, and Agentic Memory within ZoomInfo's Intelligence team.

Work alongside PMs responsible for signals and ML scoring/recommendation models.

Together, you ensure our agentic workflows fill context windows with high-quality, information-dense content exactly when needed.

Pace & Problems

Fast-moving engineering team that understands the space.

Company-wide AI adoption push creates both urgency and opportunity.

Expect interesting problems: How do we maintain sub-200ms retrieval latency at scale?

When does GraphRAG justify its indexing cost?

How do we balance context freshness with cache efficiency?

You'll shape answers that become architectural patterns across the organization.

Impact

Define a nascent discipline at a company that's already AI-first in product thinking and organizational structure.

Your architectural decisions compound,every improvement to context quality multiplies across Copilot, GTM Studio, MarketingOS, and future products we haven't imagined yet.

This is infrastructure work with direct line-of-sight to customer value.

#LI-PS1 #LI-remote

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Responsibilities: Review and score AI model responses based on criteria such as humor effectiveness, timing, engagement, and conversational naturalness (using provided rubrics). Write or revise sample responses to maximize user engagement and entertainment, while ensuring factual accuracy. Maintain consistency in Grok's personality traits across varied topics (e.g., casual chat, technical explanations, philosophical discussions, humor). Create and label training datasets focused on elements like humor, irony, banter, and cultural references. Work with engineering teams to develop evaluation tasks that test and strengthen Grok's defined personality traits.

Basic Qualifications: Advanced proficiency in English, including idioms, rhythm, tone, and nuance (native or equivalent level). Public portfolio with examples of humorous, engaging, or charismatic writing (e.g., published articles, social media threads, scripts, or viral content; provide links). Strong ability to identify tonal inconsistencies, poor pacing, or ineffective phrasing in text. Proven track record of creating writing that is consistently humorous, clever, or engaging, with evidence of broad appeal (e.g., metrics like views, shares, likes, or publications). Extensive knowledge of current internet culture (memes, trends, platforms) and historical/cultural references.

Preferred Skills and Experience: Professional experience in comedy writing, screenwriting, viral content, improvisation, or performance.

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As a Staff Software Engineer for Search Quality, you will drive the technical direction of ranking, relevance, evaluation, and quality initiatives across Databricks' next-generation Search product. You'll design and build the systems, models, and evaluation frameworks that ensure our Search stack delivers accurate, high-quality results across diverse multimodal datasets and query patterns.

The impact you will have:

• Lead the technical vision for Search Quality, shaping the ranking architecture, relevance modeling stack, and evaluation systems that power Databricks' next-generation retrieval experiences.

• Identify and solve challenges in ranking, query understanding, and hybrid retrieval , advancing state-of-the-art techniques in vector, keyword, and multimodal search.

• Design and train production-ready ranking and reranking models with strong guarantees around quality, latency, and resource efficiency.

• Partner closely with research, product, and infra teams to define metrics, evaluation methodologies, and experimentation strategies for new retrieval features and model architectures.

• Drive end-to-end engineering efforts , from early prototyping to production rollout , ensuring correctness, reliability, and measurable improvements to relevance.

• Build and operate resilient, low-latency services for ranking, evaluation, and relevance signal processing.

• Champion excellence in ML and search engineering, mentoring teammates and elevating design, code quality, and scientific rigor across the team.

• Shape Databricks' long-term roadmap for retrieval quality, ranking infrastructure, and the foundations for retrieval-driven AI products.

What we look for:

• 10+ years of experience building large-scale search, ranking, recommendation, or ML-driven relevance systems.

• Deep expertise in Search Quality, including ranking models, signals, query understanding, and evaluation methodologies.

• Strong understanding of relevance metrics and evaluation frameworks.

• Familiarity with vector search, keyword search, hybrid retrieval, and embedding-based semantic retrieval.

• Solid foundation in algorithms, data structures, and system design for performance-critical ranking and retrieval systems.

• Proven ability to deliver high-impact technical initiatives with clear business or product outcomes.

• Strong communication skills and ability to collaborate across teams in fast-moving environments.

• Strategic and product-oriented mindset with the ability to align technical execution with long-term vision.

• Passion for mentoring, growing engineers, and fostering technical excellence.

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The ideal candidate will have a strong background in supply chain management, with experience in managing a direct team and owning complex value chains from start to finish. They will be able to distill and communicate complex scenarios to executives for strategic decision-making and alignment.

Key responsibilities will include:

• Developing and executing supply & demand plans that support the company's sales forecasts and business strategies
• Leading the Supply & Demand planning team to ensure efficient and effective execution of planning activities
• Collaborating through S&OP with various departments, including sales, operations, and finance, to gather relevant data for accurate supply forecasting
• Managing inventory levels to meet service level targets while minimizing excess and obsolete inventory
• Monitoring supplier performance, ensuring timely delivery of materials, and addressing any supply chain disruptions proactively

The successful candidate will have a strong technical expertise, including ability to read technical documentation, drawings, and CAD data, understanding of a variety of hardware manufacturing processes for both electronics (PCBAs, sensor hardware, etc.) and structures/mechanisms.

We offer a highly competitive salary range of $99,000-$131,000 USD, plus highly competitive equity grants and top-tier benefits for full-time employees.

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As a senior machine learning engineer, you will play a key role in the end-to-end design and implementation of our product, which is a platform for powering use cases across training and serving of generative AI models. You will work closely with both customers and internal ML researchers to identify key areas of development for our generative AI platform.

Key responsibilities include:

• Designing and building the core platform infrastructure that supports our customer-facing product features
• Ensuring the reliability, security, and scalability of the backend distributed systems that power all aspects of our product
• Translating product requirements into user interfaces and backend distributed system design and owning end-to-end implementation

We look for:

• 4+ years of hands-on programming experience with at least one modern language such as Python, Scala, Go, or C++
• Strong sense of distributed systems design and experience building large-scale systems
• Experience building ML platform systems for applications in the ML model development lifecycle such as data preparation, model training, model evaluation, and model serving
• Direct experience developing ML models is a plus but not required
• Strong sense of end-to-end product ownership as well as intuition for both robust system design and product usability
• Effective communication skills and the ability to articulate complex technical ideas to cross-disciplinary internal and external stakeholders

Pay Range Transparency

Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above.

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We're looking for prompt and context engineers to join our product engineering team to help build AI-first products, features, and evaluations. Your mission will be to bridge the gap between model capabilities and real product experience, working with product teams to build consistent, safe, and beneficial user experiences across all product surfaces.

Key Responsibilities

• Design, test, and optimize system prompts and feature-specific prompts that shape Claude's behavior across consumer and API products.
• Build and maintain comprehensive evaluation suites that ensure model quality and consistency across product launches and updates.
• Partner closely with product teams, research teams, and safeguards to ensure new features meet quality and safety standards.
• Play a critical role in model releases, ensuring smooth rollouts and catching regressions before they impact users.
• Help build and improve the frameworks and tools that allow teams to develop and test prompts and features with confidence.
• Mentor product engineers on prompt engineering best practices and help teams build their first evaluations.
• Work in a fast-paced environment where model capabilities advance daily, requiring quick adaptation and creative problem-solving.

What We're Looking For

• 5+ years of software engineering experience with Python or similar languages.
• Demonstrated experience with LLMs and prompt engineering (through work, research, or significant personal projects).
• Strong understanding of evaluation methodologies and metrics for AI systems.
• Excellent written and verbal communication skills – you'll need to explain complex model behaviors to diverse stakeholders.
• Ability to manage multiple concurrent projects and prioritize effectively.
• Experience with version control, CI/CD, and modern software development practices.

You Might Thrive in This Role If You…

• Get excited about the nuances of how language models behave and love finding creative ways to improve their outputs.
• Enjoy being at the intersection of research and product, translating cutting-edge capabilities into user value.
• Are comfortable with ambiguity and can define success metrics for novel AI features.
• Have a strong sense of ownership and drive projects from conception to production.
• Are passionate about building AI systems that are helpful, harmless, and honest.
• Thrive in collaborative environments and enjoy teaching others.

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As a senior individual contributor, you'll be accountable for the technical decisions that ripple across the team and beyond. You'll architect the systems, tooling, and evaluation infrastructure that determine how quickly our research can move.

Responsibilities:

• Set technical direction for evaluation systems, research infrastructure, and internal tooling across the Claude Code team

• Architect eval frameworks that measure model capabilities across diverse coding tasks and scale with our research roadmap

• Lead the design of infrastructure that enables researchers to run experiments at scale, and make the foundational tradeoffs that shape how the team operates for years

• Identify the highest-leverage engineering investments,often before anyone has asked for them,and drive them to completion

• Serve as a senior technical bridge between product and research, using strong product intuition to influence which capabilities we prioritize and how we measure progress against them

• Mentor and raise the bar for other engineers on the team; review designs, unblock peers, and model the engineering standards we want to scale

• Partner with research leads to translate ambiguous research questions into durable engineering solutions

• Own critical systems end-to-end, from architecture through production reliability, and take responsibility for their long-term health

If you have 10+ years of software engineering experience, with a track record of operating as a Staff or Principal engineer (or equivalent) at a high-caliber organization, you may be a good fit for this role.

Strong candidates may also have experience with designing or scaling eval/evaluation frameworks for ML systems, reinforcement learning infrastructure or training systems, leading technical initiatives in high-performance, demanding environments, research computing, scientific infrastructure, or developer platforms at scale, a strong quantitative foundation (math, physics, or related fields), and expertise in Python and TypeScript.

The annual compensation range for this role is $405,000-$485,000 USD.

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You will help define best practices for developers building on claude for deployment to users across different developmental stages, design age-assurance policies that protect minors from inappropriate content and interactions, and establish clear boundaries for adult content and experiences. In addition, you will advise teams on opportunities for age-appropriate helpfulness, including advising cross-functional teams on beneficial use cases for younger users where appropriate.

Safety is core to our mission and you’ll help shape policy creation and development so that our users can safely interact with and build on top of our products in a harmless, helpful and honest way.

You may be a good fit if you have experience:

As a researcher, subject matter expert, or trust & safety professional working in one or more of the following focus areas: child safety, youth online safety, age assurance, developmental science, content classification and rating systems, or adult content policy.

Drafting or updating product and / or user policies, with the ability to effectively bridge technical and policy discussions.

Designing or implementing age-appropriate experiences, age assurance mechanisms, or content classification / labeling systems.

Working with generative AI products, including writing effective prompts for policy evaluations and classifier development.

Aligning product policy decisions between diverse sets of stakeholders, such as Product, Engineering, Public Policy, and Legal teams.

Understanding the challenges that exist in developing and implementing product policies at scale, including in the content moderation space.

Thinking creatively about the risks and benefits of new technologies, and leveraging data and research to inform policy recommendations.

Navigating and prioritizing work efforts amidst ambiguity.

The annual compensation range for this role is $245,000-$285,000 USD.

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You will have the opportunity to contribute directly to research projects yourself and have a direct impact on our ability to scale reward development across domains. You will work closely with researchers and translate ambiguous requirements into well-scoped engineering projects.

To be successful in this role, you should have prior research experience and be excited to work closely with researchers. You should have strong Python skills and experience with ML workflows and data pipelines, and building related infrastructure/tooling/platforms. You should be comfortable working across the stack, ranging from data pipelines to experiment tracking to user-facing tooling.

Strong candidates may also have experience with ML research, building internal tooling and platforms for ML researchers, data quality assessment and pipeline optimization, experiment tracking, evaluation frameworks, or MLOps tooling. They may also have experience with large-scale data processing, Kubernetes, distributed systems, or cloud infrastructure, and familiarity with reinforcement learning or fine-tuning workflows.

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As a research engineer, you'll partner with the product org to ensure that the vision improvements you deliver impact Claude's performance on real-world tasks. You'll also work with our product org to find solutions to our most vexing API customer challenges related to vision and spatial reasoning.

Strong candidates may also have experience with large-scale pretraining, SL, and RL on language models, deep learning research on images, video, or other modalities, developing complex agentic systems using LLMs, high-performance ML systems (GPUs, TPUs, JAX, PyTorch), and large-scale ETL and data pipeline development.

The annual compensation range for this role is $350,000-$850,000 USD.

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You'll be responsible for leading and growing the DACH Applied AI Architect team, establishing processes and best practices for your segment's pre-sales engagements based on your depth of experience and knowledge of the market, helping each team member achieve success, high productivity, and career growth, and representing Anthropic as a technical lead on some of its most important partnerships.

In collaboration with Sales, Product, and Engineering teams, you'll help large enterprise customers incorporate leading-edge AI systems into both internal business transformation initiatives and customer-facing products. You will also help build technical GTM plays for Anthropic’s products and define high-value industry solutions.

Responsibilities:

• Hire, manage and mentor a team of Applied AI Architects for DACH, providing both technical guidance and career development
• Set goals and reviews for your team, promoting growth and output
• Work with a handful of highest-value enterprise customers on their overall AI adoption strategies, focusing on pre-sales technical excellence including use case scoping, architecture reviews, technical champion building, technical adoption workshops and POC execution
• Partner closely with your aligned GTM leadership to understand customer requirements and co-build GTM strategies to drive adoption across all industry verticals
• Own the technical portions of pre-sales engagements, ensuring your team provides compelling demos and validates customer ROI from Anthropic products
• Develop scalable technical engagement frameworks and reusable assets tailored for all non-tech sectors, including Financial Services & Insurance, Healthcare, Telco, Retail and others.
• Drive collaboration from cross-functional teams to influence and unify stakeholders at all levels of the organization to drive business outcomes
• Travel to customer sites for executive-level sessions, technical workshops, and building relationships
• Establish a shared vision for creating solutions that enable beneficial and safe AI
• Lead the vision, strategy, and execution of innovative solutions that leverage our latest models' capabilities
• Contribute to thought leadership through conference presentations, webinars, and technical content creation
• Stay current with emerging AI/ML trends and competitive landscape across all major Industries verticals

You may be a good fit if you have:

• 7+ years of experience as an Solutions Architect, Sales Engineer, or similar pre-sales technical role
• 3+ years of technical go-to-market management experience, specifically managing pre-sales teams
• Experience working with and selling to large enterprise customers across multiple verticals
• Demonstrated ability to navigate and articulate complex technical, organisational and regulatory requirements of large enterprises, in particular in regulated industries (e.g FSI, Healthcare & Life Sciences)
• A proven knowledge of the DACH market and its local specificities (regulatory, cultural, technical…)
• Experience framing and delivering enterprise AI use cases (productivity, workflow transformation) and or scoping large enterprise adoption programs
• Deep technical proficiency with enterprise AI deployments, API integrations, and production LLM use cases
• Demonstrated ability to build scalable, repeatable processes and frameworks that work across diverse customer segments
• An organisational mindset and enjoy building foundational teams in a relatively unstructured environment
• Excellent communication, collaboration, and coaching abilities
• Comfort dealing with highly uncertain, ambiguous, and fast-moving environments
• Strong executive presence and ability to foster deep relationships with technical leaders and engineering teams
• High-level familiarity with the architecture and operation of LLM and/or ML in general
• Experience with prompt engineering, LLM evaluation, and architecting AI-powered systems
• Ability to make ambiguous problems clear and identify core principles that can translate across scenarios
• A passion for making powerful technology safe and societally beneficial
• Creative thinking about the risks and benefits of new technologies, beyond past checklists and playbooks
• A track record of staying current with emerging AI research and industry trends

Strong candidates may also have:

• 10+ years technical experience
• 5+ years managing AI technical teams in hypergrowth (ideally from 0 to 30+)
• Previous experience leading solutions architect or pre-sales teams through rapid growth
• Proven experience and understanding across all key non-tech industry verticals, in particular the regulated industries: Financial Services, Insurance, Healthcare, Life Sciences, Telco, Retail, Consumer Goods, Manufacturing, Oil & Gas, etc.
• In addition to English, native or fluency in a DACH language
• Demonstrated experience in defining and delivering enterprise AI use cases in regulated industries: e.g Banking, Insurance, Healthcare and Life sciences
• Track record building technical playbooks and assets that scale across diverse customer segments
• Understanding of both digital-native technical requirements (API integration, developer experience) and traditional enterprise needs (security, compliance, change management)
• Background at enterprise AI software or API-first companies serving large enterprise customers
• Proven experience building a DACH AI team

Logistics

Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

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Join the team as Twilio's next Software Engineer L3. This position is that of a Senior Software Engineer to join Twilio's Messaging Compliance Onboarding team. Programmable Messaging is Twilio's biggest product. To keep pace with the evolving messaging compliance ecosystem, we need strong engineers that can create innovative solutions to ensure compliance with Twilio partners.

In this role, you'll build and maintain multiple compliance program workflows, carrier/ecosystem integrations and customer interactions in the Compliance domain. You will design and develop elegant and scalable solutions across a wide variety of compliance program types including frontend UI experiences and backend APIs, that are highly available and responsive.

You will work through ambiguity, deliver quickly and with a high quality. Build towards achieving the next generation of architecture vision that empowers expansion of Compliance programs. Interact cross functionally across engineering teams within Twilio to align and build the product and architecture vision.

Twilio values diverse experiences from all kinds of industries, and we encourage everyone who meets the required qualifications to apply. If your career is just starting or hasn't followed a traditional path, don't let that stop you from considering Twilio.

We are always looking for people who will bring something new to the table!

*Required:

• 5+ years of experience and a strong fundamental knowledge of software development using JVM languages.

• Experience building web services incorporating best practices for external systems integration, including defensive and hardened approaches to mitigate downstream issues.

• Experience working with highly scalable APIs, high volume data pipelines and large distributed systems.

• Maintaining and operating cloud services.

• An unwillingness to settle for 'good enough', instead staying focused on longevity through well-tested code and continuous improvement.

• Demonstrated commitment to seeking diverse viewpoints and acting with intention to create an inclusive team environment.

• Excellent written and verbal communication skills. Ability to write down and present designs and decisions throughout the development lifecycle, collaborating with engineering and non-engineering roles.

Desired:

• 5+ years of Engineering experience, developing and maintaining high traffic services.

• Familiarity with DynamoDB, SQS, and data integration services like AWS glue

• Familiarity with LLMs, prompt optimizations to improve model accuracy, setting up evaluation pipelines

• Familiarity with Kubernetes, Temporal or similar workflow orchestration

• Experience working with frontend libraries like React or similar.

Compensation:

*Please note this role is open to candidates outside of California, Colorado, Hawaii, Illinois, Maryland, Massachusetts, Minnesota, New Jersey, New York, Vermont, Washington D.C., and Washington State.

The estimated pay ranges for this role are as follows:

• Based in Colorado, Hawaii, Illinois, Maryland, Massachusetts, Minnesota, Vermont or Washington D.C.: $138,700 - $173,400

• Based in New York, New Jersey, Washington State, or California (outside of the San Francisco Bay area): $146,800 - $183,600

• Based in the San Francisco Bay area, California: $163,100 - $203,900.

This role may be eligible to participate in Twilio's equity plan and corporate bonus plan. All roles are generally eligible for the following benefits: health care insurance, 401(k) retirement account, paid sick time, paid personal time off, paid parental leave.

Applications for this role are intended to be accepted until 4/10/2026, but may change based on business needs.

Twilio thinks big. Do you? We like to solve problems, take initiative, pitch in when needed, and are always up for trying new things. That's why we seek out colleagues who embody our values , something we call Twilio Magic. Additionally, we empower employees to build positive change in their communities by supporting their volunteering and donation efforts. So, if you're ready to unleash your full potential, do your best work, and be the best version of yourself, apply now!

If this role isn't what you're looking for, please consider other open positions.

Twilio is proud to be an equal opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Qualified applicants with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Additionally, Twilio participates in the E-Verify program in certain locations, as required by law.

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Working closely with our Post-Sales, Product, and Engineering teams, you'll combine engineering expertise, an understanding of frontier AI applications, and customer-facing skills to understand customer workflows and develop innovative solutions that address complex business challenges while maintaining our high standards for safety and reliability.

Responsibilities:

• Work within customer systems to build production applications with Claude models, ensuring that these products meet customer requirements.
• Deliver technical artifacts for customers like MCP servers, sub-agents, and agent skills that will be used in production workflows.
• Provide white-glove deployment support for Anthropic products in enterprise environments.
• Identify and codify repeatable deployment patterns and contribute insights back to our Product and Engineering teams.
• Maintain strong knowledge of the latest developments in LLM capabilities, implementation patterns, and AI product development stacks.
• Build long-term relationships with customers and proactively identify new opportunities for AI deployment throughout the lifecycle of an engagement.
• Potential travel (based on location) to customer sites to build in-person with customers.

Requirements:

• 3+ years of experience in a technical, customer-facing role such as Forward Deployed Engineer, or as a Software Engineer with consulting experience.
• Production experience with LLMs including advanced prompt engineering, agent development, evaluation frameworks, and deployment at scale.
• Strong programming skills with proficiency in Python (and ideally in one or more additional languages like Typescript, Java, etc) and experience shipping production applications.
• High agency with an ability to navigate ambiguity present in complex organizations.
• High cooperation mindset for cross-organizational collaboration, balancing competing priorities with integrity.
• Passion for advancing safe, beneficial AI systems through creative technical applications.
• Strong communication skills to conduct discovery with customers and to convey technical concepts to diverse stakeholders while maintaining a low ego and collaborative approach.

Benefits:

• Annual salary: $200,000-$300,000 USD
• Competitive compensation and benefits
• Optional equity donation matching
• Generous vacation and parental leave
• Flexible working hours
• Lovely office space in which to collaborate with colleagues

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You will build and lead a team of Partner Solutions Architects, establish processes and best practices for partner-led pre-sales engagements, and represent Anthropic as the technical lead on its most important partnerships. In collaboration with Sales, Partnerships, Product, and Engineering, you will help partners incorporate leading-edge AI into their practices, accelerate indirect revenue, and execute long-term GTM strategy while maintaining our best-in-class safety standards.

Responsibilities:

Team Leadership & Development: Hire, manage, and mentor a team of Partner Solutions Architects. Set goals, run reviews, and coach each team member toward high productivity and career growth.

Strategic Technical Partnership: Act as the senior technical thought partner to Anthropic's GTM partnerships team. Co-build partner strategy with aligned GTM leadership, drive key programs, and align cross-functional stakeholders (Sales, Product, Engineering) behind partner outcomes.

Partner Enablement & Ecosystem: Embed your team with GSI and cloud partner technical teams to enable their AI practices, troubleshoot, and evangelize Anthropic in their developer communities. Represent Anthropic at partner events (GSI workshops, AWS/GCP summits, hackathons) and contribute technical content and thought leadership.

Joint Solution Development: Lead partners in identifying high-value, industry-specific GenAI applications. Develop joint solutions and codify reference architectures and best practices to accelerate time to deployment.

Customer Deal Support: Own the technical portion of partner-led pre-sales engagements. Intervene directly on strategic deals where partners are the primary delivery vehicle, providing deep solution architecture guidance.

Product Feedback: Gather and validate feedback on Anthropic's products from partner deployments and deliver it to Product and Engineering to inform roadmap and partner strategy.

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Head of Solutions Architects, Applied AI (Korea)

About Anthropic

Anthropic's mission is to create reliable, interpretable, and steerable AI systems. The company is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

About the Role

As the founding leader of Applied AI Solutions Architecture in Korea, you will drive the adoption of frontier AI by enabling the deployment of Anthropic's products (Claude for Enterprise, Claude Code, and API) across Korean enterprises and digital-first organisations. You'll leverage your technical skills and consultative sales experience to drive positive AI transformation that addresses our customers' business needs, meets their technical requirements, and provides a high degree of reliability and safety.

Responsibilities

• Build and manage the foundational team of Applied AI professionals in Seoul (Solutions Architects and Product Engineers) providing both technical guidance and career development
• Set goals and reviews for your team, promoting growth and output
• Work with a handful of highest-value enterprise customers on their overall AI adoption strategies, focusing on pre-sales technical excellence including use case scoping, technical champion building, and POC execution
• Partner closely with your aligned GTM leadership to understand customer requirements & co-build GTM strategies to drive adoption for Korean enterprise customers
• Contribute to thought leadership through conference presentations, webinars, and technical content creation
• Own the technical portions of pre-sales engagements, ensuring your team provides compelling demos and validates enterprise customer ROI from Anthropic products
• Drive collaboration from cross-functional teams to influence and unify stakeholders at all levels of the organisation to drive business outcomes
• Travel regularly to customer sites for executive-level sessions, technical workshops, and building relationships
• Establish a shared vision for creating solutions that enable beneficial and safe AI in technology products
• Lead the vision, strategy, and execution of innovative solutions that leverage our latest models' capabilities
• Stay current with emerging AI/ML trends and competitive landscape in the Korean enterprise tech sector

Requirements

• 7+ years of experience as a Solutions Architect, Sales Engineer, or similar pre-sales technical role
• 3+ years of technical go-to-market management experience, specifically managing pre-sales teams
• Native or business-level fluency in Korean and professional proficiency in English
• Experience working with Korean enterprise customers and understanding local business culture and decision-making processes
• Experience with the unique technical requirements and technical procurement process of enterprise tech companies
• Deep technical proficiency with enterprise AI deployments, API integrations, and production LLM use cases
• Have an organisational mindset and enjoy building foundational teams in a relatively unstructured environment
• Have excellent communication, collaboration, and coaching abilities
• Are comfortable dealing with highly uncertain, ambiguous, and fast-moving environments typical of the tech industry
• Strong executive presence and ability to foster deep relationships with technical leaders and engineering teams
• Have at least a high level familiarity with the architecture and operation of large language models and/or ML in general
• Experience with prompt engineering, LLM evaluation, and architecting AI-powered systems
• Make ambiguous problems clear and identify core principles that can translate across scenarios
• Have a passion for making powerful technology safe and societally beneficial
• Think creatively about the risks and benefits of new technologies, and think beyond past checklists and playbooks
• Stay up-to-date and informed by taking an active interest in emerging research and industry trends
• Understanding of developer tooling, SDKs, and technical integration patterns common in enterprise tech companies

Benefits

• Competitive salary and benefits package
• Opportunity to work with a talented and diverse team
• Professional development and growth opportunities
• Flexible work arrangements

How to Apply

If you're interested in this opportunity, please submit your resume and a cover letter explaining why you're a great fit for this role. We can't wait to hear from you!

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About Anthropic

Anthropic's mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole.

Responsibilities:

Serve as a technical advisor to Anthropic customers as they deploy new products & workflows with our models: from discovery through deployment, coordinating internally across multiple teams to drive customer success

Partner with account executives to deeply understand customer product requirements and architect technical solutions, ensuring alignment between business objectives and technical implementation

Guide technical architecture decisions and help customers build state-of-the-art products & workflows with LLMs via API

Develop customized pilots, prototypes, and evaluation suites that make the case for customer deployment of our models into customer products and workflows via our API

Lead hands-on technical workshops and code reviews with customer engineering teams

Identify common design patterns and contribute insights back to our Product and Engineering teams

Maintain strong knowledge of the latest developments in LLM capabilities, implementation patterns, and AI product development stacks

Travel occasionally to customer sites for workshops, implementation support, and building relationships

Attend conferences, lead speaking engagements, write blog posts and white papers on topics surrounding the AI space

Requirements:

4+ years of experience in a technical roles such as Customer Engineer, Forward Deployed Engineer, Software Engineer or Technical Product Manager with a desire to work closely with customers

Production experience with LLMs including advanced prompt engineering, agent development, evaluation frameworks, and deployment at scale

Strong programming skills with proficiency in Python and experience building production applications

Expertise working with common LLM implementation patterns, prompt engineering, evaluation frameworks, agent frameworks, and retrieval frameworks.

Ability to navigate ambiguity and execute across domains with intellectual openness, finding simple solutions to complex problems

High cooperation mindset for cross-organizational collaboration, balancing competing priorities with integrity

Passion for advancing safe, beneficial AI systems through creative technical applications

Exceptional communication skills to convey technical concepts to diverse stakeholders while maintaining a low ego and collaborative approach

Fluent in both Korean and English

Logistics:

Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience

Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience

Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position

Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

How we're different:

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact , advancing our long-term goals of steerable, trustworthy AI , rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.

Come work with us!

Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.

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Your responsibilities will include:

• Leading, growing, and mentoring a globally distributed team of Architects supporting mission-driven non-profits across education, global health, economic mobility, and life sciences
• Setting the vision, strategy, and operating model for how Applied AI shows up in Beneficial Deployments
• Establishing hiring plans, team structure, and career development paths as we scale the team globally
• Partnering closely with segment leads and senior partner leadership to understand requirements and shape engagements on our highest-impact partnerships
• Driving the design of cohort-based accelerators, Claude Code enablement programs, and other scalable mechanisms that multiply our impact across many organisations simultaneously

You may be a good fit if you have:

• 10+ years of experience in technical, customer-facing roles (Solutions Architect, Forward Deployed Engineer, Customer Engineer, Sales Engineer, or similar), with meaningful exposure to complex, high-stakes deployments
• 7+ years of engineering or technical leadership experience, preferably building and scaling customer-facing or forward-deployed teams globally
• Experience working with or inside mission-driven organisations,education, healthcare, scientific research, global development, or non-profits,and a genuine understanding of the constraints, incentives, and operating realities of these sectors
• Familiarity with common LLM implementation patterns, including prompt engineering, evaluation frameworks, agent frameworks, and retrieval systems; working knowledge of Python

Strong candidates may also have:

• Experience leading globally distributed teams across time zones and regions
• Background in philanthropy, global health, education technology, or scientific research
• Experience designing cohort-based or programmatic delivery models that scale technical expertise across many organisations
• A working understanding of emerging research in agents, evaluations, and AI safety

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