This is a fully remote, 1099 independent contractor opportunity with an estimated duration of six months and the potential for extension. To be eligible, candidates must be authorised to work in the United States; visa sponsorship is not available for this role.

About the Program

The Human Frontier Collective (HFC) Fellowship brings together top researchers and domain experts to collaborate on high-impact work that are shaping the future of AI. As an HFC Fellow, you’ll apply your academic and professional expertise to help design, evaluate, and interpret advanced generative AI systems,while gaining exposure to cutting-edge research and working alongside an interdisciplinary network of leading thinkers.

Responsibilities

• Collaborative Work: Get invited to engage in high-impact projects with our partnered AI labs and platforms. Design complex clinical scenarios, evaluate model decision-making for safety and accuracy, and shape reasoning frameworks through structured, example-driven feedback.
• HFC Community: Beyond the work, you’ll become part of a supportive, interdisciplinary network of innovators and thought leaders committed to advancing frontier AI across domains.
• Contribute to Research Publications: Collaborate with Scale’s research team to co-author technical reports and research papers,boosting your academic visibility and professional recognition (e.g., SciPredict, PropensityBench, Professional Reasoning Benchmark).

Requirements

• Education: Medical degree required (MD, DO) with board certification; open to residents, practicing clinicians, or those with extensive clinical experience.
• Specialties: Internal medicine, emergency medicine, radiology, surgery, psychiatry, and related fields.
• Skills: Strong clinical reasoning and writing skills, with the ability to assess complex, nuanced, or edge-case scenarios.
• Professional Mindset: Detail-oriented, innovative thinker with a passion for financial technology and a commitment to collaboration. Prior experience with AI is not required, but a plus.

Benefits

• Advance Medical AI Solutions: Apply your clinical expertise to tackle complex, real-world healthcare challenges where your judgment shapes advanced AI reasoning and patient care decisions.
• Professional Development: High-impact medical experts expand their influence through review projects, advisory roles, and research,while deepening their AI expertise, enhancing clinical reasoning skills, and gaining hands-on experience with cutting-edge healthcare AI technologies.
• Join a Top-Tier Network: Collaborate with a global network of academics and experts to advance responsible AI through impactful, flexible research and training. 80% of our members come from leading institutions.
• Flexible Schedule: Set your own schedule, with flexible 10–40 hour weeks that fit around your life and other commitments.
• Competitive Pay: Project pay rates vary across platforms and are depending on a number of factors, including but not limited to; projects, scope, skillset, and location.

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This high-impact role will drive the technical direction and oversight for Deep Research Agent Development, translating cutting-edge research in Generative AI, Large Language Models (LLMs), and Agentic Frameworks into robust, scalable, and high-impact production systems that enhance enterprise operations, analytics, and core efficiency.

The ideal candidate thrives in a fast-paced environment, has a passion for both deep technical work and mentoring, and is capable of setting a long-term technical strategy for a critical domain while maintaining a strong, hands-on delivery focus.

Responsibilities

Technical Leadership & Vision

• Set the Technical Roadmap: Define and own the technical strategy, architecture, and roadmap for Deep Research Agents for the Enterprise, ensuring alignment with Scale AI’s overall AI strategy and business goals.

• Drive Breakthrough Research to Production: Lead the end-to-end development, from initial research to production deployment, to landing on customer impact, with a focus on integrating diverse data modalities.

• Core Agent Capabilities Development:

Advanced Knowledge Retrieval: Architect and implement state-of-the-art retrieval systems to ensure the agents provide accurate and comprehensive answers from public and proprietary data sources from enterprises.

Data Analysis: Design and champion the development of data analysis agents that accurately translate complex natural language queries into executable SQL/code against diverse enterprise data schemas.

Multimodal Intelligence: Lead the integration of Multimodal AI capabilities to process and extract structured information from visual documents, tables, and forms, enriching the agent's knowledge base.

Architecture & Design: Design and champion highly scalable, reliable, and low-latency infrastructure and frameworks for building, orchestrating, and evaluating multi-agent systems at enterprise scale.

Technical Excellence: Serve as the technical authority for the team, leading design reviews, defining ML engineering best practices, and ensuring code quality, security, and operational excellence for all agent systems.

Team Leadership & Mentorship

• Lead and Mentor: Technically lead and mentor a team of Machine Learning Engineers and Research Scientists, fostering a culture of innovation, rigorous engineering, rapid iteration, and technical depth.

• Recruiting & Growth: Partner with management to hire, onboard, and grow top-tier talent, helping to shape the long-term structure and capabilities of the team.

• Cross-Functional Influence: Collaborate effectively with Product Managers, Data Scientists, and other engineering/science teams to translate ambiguous, high-level business problems into concrete, executable technical specifications and impactful agent solutions.

Basic Qualifications

• Bachelor's degree in Computer Science, Electrical Engineering, a related field, or equivalent practical experience.

• 8+ years of experience in software development, with at least 6 years focused on Machine Learning, Deep Learning, or Applied Research in a production environment.

• 2+ years of experience in a formal or informal Technical Leadership role (Team Lead, Tech Lead) with a focus on setting technical direction for a domain.

• Deep expertise in Generative AI and Large Language Models (LLMs).

• Demonstrated experience designing, building, and deploying AI Agents or complex Agentic systems in production at scale.

• Experience with large-scale distributed systems and real-time data processing.

Preferred Qualifications

• Advanced degree (Master's or Ph.D.) in Computer Science, Machine Learning, or a related quantitative field.

• Demonstrated experience designing and deploying production-grade Text-to-SQL systems, including handling complex schema linking and query optimization.

• Practical experience with Multimodal AI, specifically integrating OCR and vision-language models for document intelligence and structured data extraction from images/forms.

• Proven experience in one or more relevant deep research areas: Reinforcement Learning (RL), Reasoning and Planning, Agentic Systems.

• Experience with vector databases and advanced retrieval techniques.

• A track record of publishing research papers in top-tier ML/AI conferences (e.g., NeurIPS, ICML, ICLR, KDD).

• Excellent written and verbal communication skills, with the ability to articulate complex technical vision to executive stakeholders and technical peers.

• Experience driving cross-team technical initiatives that have delivered significant business impact.

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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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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You will work closely with Scale’s ML teams and researchers to build the foundation platform which supports all our ML research and development works. You will be building and optimising the platform to enable our next generation LLM training, inference and data curation.

Key responsibilities include:

• Building, profiling and optimising our training and inference framework.
• Collaborating with ML and research teams to accelerate their research and development, and enable them to develop the next generation of models and data curation.
• Researching and integrating state-of-the-art technologies to optimise our ML system.

The ideal candidate will have:

• Passionate about system optimisation.
• Experience with multi-node LLM training and inference.
• Experience with developing large-scale distributed ML systems.
• Experience with post-training methods like RLHF/RLVR and related algorithms like PPO/GRPO etc.
• Strong software engineering skills, proficient in frameworks and tools such as CUDA, PyTorch, transformers, flash attention, etc.

Nice to haves include demonstrated expertise in post-training methods and/or next generation use cases for large language models including instruction tuning, RLHF, tool use, reasoning, agents, and multimodal, etc.

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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At Scale AI, our mission is to accelerate the development of AI applications. This role is at the intersection of cutting-edge AI research and practical application, with a focus on studying the data types essential for building state-of-the-art agents.

Responsibilities

• Explore the data landscape needed to advance intelligent, adaptable AI agents, guiding the data strategy at Scale to drive innovation.
• Contribute to impactful research publications on agents, collaborate with customer researchers, and work alongside the engineering team to translate these advancements into real-world, scalable 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 venues (e.g., ACL, EMNLP, NAACL, NeurIPS, ICML, ICLR, COLM, etc.).
• At least three years of experience addressing sophisticated ML problems, either in a research setting or product development.

Nice to Have

• Hands-on experience with open source LLM fine-tuning or involvement in bespoke LLM fine-tuning projects using Pytorch/Jax.
• Hands-on experience and publications in building applications and evaluations related to AI agents such as tool-use, text2SQL, browser agents, coding agents and GUI agents.
• Hands-on experience with agent frameworks such as OpenHands, Swarm, LangGraph, etc.
• Familiarity with agentic reasoning methods such as STaR and PLANSEARCH
• Experience working with cloud technology stack (eg. AWS or GCP) and developing machine learning models in a cloud environment.

Benefits

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

Salary Range

$259,200-$324,000 USD

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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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Scale's ML platform (RLXF) team builds our internal distributed framework for large language model training and inference. The platform has been powering MLEs, researchers, data scientists and operators for fast and automatic training and evaluation of LLM's, as well as evaluation of data quality.

At Scale, we're uniquely positioned at the heart of the field of AI as an indispensable provider of training and evaluation data and end-to-end solutions for the ML lifecycle. You will work closely across Scale's ML teams and researchers to build the foundation platform that supports all our ML research and development. You will be building and optimizing the platform to enable our next generation of LLM training, inference and data curation.

Responsibilities:

• Build, profile and optimize our training and inference framework
• Collaborate with ML teams to accelerate their research and development and enable them to develop the next generation of models and data curation
• Research and integrate state-of-the-art technologies to optimize our ML system

Ideal Candidate:

• Strong excitement about system optimization
• Experience with multi-node LLM training and inference
• Experience with developing large-scale distributed ML systems
• Strong software engineering skills, proficient in frameworks and tools such as CUDA, Pytorch, transformers, flash attention, etc.
• Strong written and verbal communication skills and the ability to operate in a cross functional team environment

Nice to Have:

• Demonstrated expertise in post-training methods &/or next generation use cases for large language models including instruction tuning, RLHF, tool use, reasoning, agents, and multimodal, etc.

Compensation Packages:

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.

Please note that our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.

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This is a fully remote, 1099 independent contractor opportunity with an estimated duration of six months and the potential for extension. To be eligible, candidates must be authorized to work in the country they reside in.

About the Programme

The Human Frontier Collective (HFC) Fellowship brings together top researchers and domain experts to collaborate on high-impact work that are shaping the future of AI. As an HFC Fellow, you’ll apply your academic and professional expertise to help design, evaluate, and interpret advanced generative AI systems,while gaining exposure to cutting-edge research and working alongside an interdisciplinary network of leading thinkers.

Responsibilities

• Collaborative Work: Get invited to engage in high-impact projects with our partnered AI labs and platforms. Design complex clinical scenarios, evaluate model decision-making for safety and accuracy, and shape reasoning frameworks through structured, example-driven feedback.
• Join the HFC Community: Beyond the work, you’ll become part of a supportive, interdisciplinary network of innovators and thought leaders committed to advancing frontier AI across domains.
• Contribute to Research Publications: Collaborate with Scale’s research team to co-author technical reports and research papers,boosting your academic visibility and professional recognition (e.g., SciPredict, PropensityBench, Professional Reasoning Benchmark).

Eligibility

• Education: Medical degree required (MD, DO) with board certification; open to residents, practicing clinicians, or those with extensive clinical experience.
• Specialties: Internal medicine, emergency medicine, radiology, surgery, psychiatry, and related fields.
• Skills: Strong clinical reasoning and writing skills, with the ability to assess complex, nuanced, or edge-case scenarios.
• Professional Mindset: Detail-oriented, innovative thinker with a passion for financial technology and a commitment to collaboration. Prior experience with AI is not required, but a plus.

Benefits

• Advance Medical AI Solutions: Apply your clinical expertise to tackle complex, real-world healthcare challenges where your judgment shapes advanced AI reasoning and patient care decisions.
• Professional Development: High-impact medical experts expand their influence through review projects, advisory roles, and research,while deepening their AI expertise, enhancing clinical reasoning skills, and gaining hands-on experience with cutting-edge healthcare AI technologies.
• Join a Top-Tier Network: Collaborate with a global network of academics and experts to advance responsible AI through impactful, flexible research and training. 80% of our members come from leading institutions.
• Flexible Schedule: Set your own schedule, with flexible 10–40 hour weeks that fit around your life and other commitments.
• Competitive Pay: Project pay rates vary across platforms and are depending on a number of factors, including but not limited to; projects, scope, skillset, and location.

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This is an individual contributor role with heavy leadership expectations. You are the 'CEO of the Account', responsible for the following:

• Full-Spectrum Capture & Quota Ownership: Carry and exceed a multi-million dollar annual revenue quota.
• Tactical Execution: You don't just delegate; you execute. You will personally draft high-impact white papers, lead the development of complex proposals, architect deal structures, and navigate the nuances of defence contracting.
• Operational Transition: Once the deal is signed, your job isn't over. You will continue to lead the account, ensuring that the delivery team enables mission success.
• Renewal, Expansion, & Growth: Own the long-term account strategy. You are responsible for identifying the next use case, securing the follow-on funding, and driving the 10x growth that turns a single deployment into a department-wide enterprise standard.
• Direct Agentic Solutioning: Work in the weeds with technical teams and end-users to co-design Agentic AI workflows.
• SI & Prime Orchestration: In partnership with Scale's Partner Managers, you will actively manage and negotiate with Tier 1 Systems Integrators (SIs) and Defence Primes to ensure Scale is the agentic AI engine of their larger programmes.

You will be responsible for identifying and pursuing new business opportunities, developing and executing sales strategies, and building and maintaining strong relationships with key stakeholders.

The ideal candidate will have a strong background in sales, a deep understanding of the defence industry, and excellent communication and interpersonal skills.

This role is eligible to earn commissions.

Compensation packages at Scale 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.

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.

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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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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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This role demands deep technical expertise in backend architecture and the ability to influence decisions across the team and adjacent engineering groups. You will thrive in a fast-paced, zero-to-one environment, cutting through ambiguity to drive product-market fit.

In practice, that means using AI tools for architectural reasoning and design review, generating and validating test coverage, accelerating code review cycles, and helping engineers build judgment about when AI output is trustworthy and when it isn't.

You'll define what 'good' looks like here and bring the team along. You'll also be a force multiplier - mentoring senior engineers, raising the technical bar through architecture.

Proactively shape the technical strategy and architecture of a greenfield VDC identity ecosystem, partnering with principal engineers to ensure decisions prioritize open standards and interoperability.

Own architectural decisions in a fast-moving environment - balancing rapid delivery with long-term scalability, security, and platform integrity.

Identify and mitigate technical risks before they become blockers; escalate dependencies early and widely.

Own production health for your systems - incident response, root cause identification, and driving operational improvement projects (monitoring coverage, alert reduction, runbook quality).

Champion high engineering standards across the team, including rigorous code reviews, comprehensive unit/functional testing, and architectural review processes to ensure the platform is tamper-proof.

Drive continual evolution in the adoption of AI-native development practices, helping the team rethink how we design, review, and ship software with AI as a core part of the workflow.

Proactively identify and prioritize tech debt; drive improvements in areas beyond feature work - CI/CD, observability, documentation, reliability, and support processes.

Partner with Product and Design to understand and own the desired customer outcome, not just the technical deliverable.

Actively invest in the growth of peer engineers, taking responsibility for raising the technical bar of the team as a whole.

Operates well beyond basic AI tool usage - understands how to apply AI meaningfully across the full software development lifecycle, can evaluate and adopt new AI tooling with good judgment, and is able to establish practices and bring a team along.

Proven experience defining scalable backend architectures and integrating complex APIs with modern web technologies - including the ability to make and defend architectural decisions with lasting org-wide impact.

Solid understanding of web authentication and authorization fundamentals - how auth flows work, token-based access (JWT, OAuth), and best practices for securing sensitive user data.

Deep expertise in building highly reliable, secure, enterprise-grade software using Java or Node.js.

Proficiency in JavaScript or TypeScript, with the ability to navigate and contribute to the frontend to unblock feature development.

Strong understanding of cloud architecture principles, with experience designing and operating large-scale services on AWS.

Hands-on experience with identity protocols such as OIDC4VP, OIDC4VCI, OAuth, and the W3C Verifiable Credentials data model.

Prior experience leading a team of engineers through a meaningful shift in ways of working - whether around AI adoption, developer tooling, or engineering culture change.

Practical knowledge of cryptography: public/private key infrastructure (PKI), digital signatures, and hashing, particularly in the context of Verifiable Credentials or DIDs.

Experience building or maintaining publicly released SDKs used by external developers.

Experience in one of the following areas is preferred: developing Identity and Access Management (IAM) tooling, working with blockchain technology, or contributing to a 'zero-to-one' startup-like team.

The annual base salary range for this position for candidates located in Canada is between $160,000-$220,000 CAD.

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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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You will collaborate closely with our technical teams to support the development and refinement of new AI capabilities, with a particular emphasis on quantitative trading domains.

Your expertise will help select and solve challenging problems in systematic and quantitative strategies , including statistical arbitrage, factor investing, market microstructure modeling, high-frequency / execution algorithms, risk premia harvesting, machine learning-based alpha generation, and portfolio optimisation under realistic constraints.

This role requires strong analytical thinking, rapid adaptation to evolving guidelines, and the ability to provide rigorous, technically sound critiques and solutions in a fast-moving environment.

As a Quantitative Trader, you will directly contribute to xAI's mission by helping train and refine our frontier AI models.

You will teach the models how quantitative traders reason, model markets, evaluate signals, manage risk, and interact with complex financial data and systems.

This involves providing high-quality data in various formats (text, voice, video), writing detailed annotations, critiquing model outputs, recording audio explanations, and occasionally participating in structured video sessions.

We are looking for individuals who are enthusiastic about these data-generation activities, as they form a core part of advancing xAI’s goals in scientific discovery and real-world reasoning.

Quantitative Traders provide labeling, annotation, evaluation, and expert reasoning services across text, voice, and video data modalities to support model training and evaluation.

The role may include recording audio responses, participating in video-based tasks, or producing step-by-step quantitative reasoning traces , all of which are essential job functions required to fulfill xAI’s mission.

All outputs are considered work-for-hire and owned by xAI.

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The Technical Advisor Specialist (Part-Time Internship) role is a summer semester opportunity designed for university students, ideally with experience in competitive coding, mathematics, and STEM disciplines.

These Specialists will immerse themselves in real-world projects that push the boundaries of generative AI, gaining firsthand exposure to cutting-edge research and technology.

Throughout the program, you’ll have the freedom to work flexibly around your academic schedule, the chance to connect directly with AI experts, and the support of a team that values your contributions and professional growth.

What You'll Do

• Contribute to Cutting-Edge AI Projects: Work on initiatives aimed at advancing AI capabilities,such as training models for complex reasoning tasks or identifying model failure modes.

You’ll gain exposure to state-of-the-art technologies and research, enhancing your technical expertise.

• Join Focus Groups: Participate in bi-weekly sessions where you’ll exchange insights, discuss evolving AI techniques, and learn from experienced researchers.

This forum encourages deep exploration of topics and helps you develop critical thinking and communication skills.

• Engage in Team-Based Projects: Collaborate with small groups of specialists on creative challenges,ranging from drafting blog-style content to conceptualizing innovative AI solutions.

By working closely with peers, you’ll refine your teamwork, leadership, and problem-solving abilities.

• Work Independently & Flexibly: Set your own working hours, ensuring you can prioritize your academic life while still making meaningful progress.

The environment is structured to accommodate your schedule without compromising the quality of your contributions.

Who Should Apply

• Academic Background: Enrolled students in computer science, mathematics, engineering, or a related STEM field.

• Technical Skills: Demonstrated coding proficiency, strong analytical abilities, or experience with competitive math or programming competitions.

• Mindset: Curious, self-motivated, and eager to learn, contribute, and collaborate with like-minded peers and industry experts.

Why Join Us?

• Real-World Impact: Your work will have tangible influence on the direction of AI capabilities, giving you a sense of purpose and involvement that goes beyond typical internship work.

• Professional Growth & Networking: Connect one-on-one with AI professionals, build relationships with fellow specialists, and expand your industry network.

• Optional In-Person Meetups: Opt to join occasional regional gatherings to meet peers and Scale AI personnel face-to-face.

These events provide opportunities for more personal interactions, fostering deeper connections and insights that complement your remote work.

• Pathways to the Future: Exceptional specialists may be invited to continue working with Scale AI.

Alumni networks and ongoing support keep doors open for future collaborations and career advancement.

• Compensation & Flexibility: $50/hour; 5-20 hours a week, and fully remote (within the U.S.)

Notes

Our policy requires a 90-day waiting period before reconsidering candidates for the same role.

This allows us to ensure a fair and thorough evaluation of all applicants.

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Your responsibilities will include evaluating and refining AI-generated code, ensuring it adheres to industry standards for efficiency, scalability, and reliability. You will also collaborate with cross-functional teams to enhance AI-driven coding solutions, ensuring they meet enterprise-level quality and performance benchmarks.

To succeed in this role, you will need professional software engineering experience building scalable, high-performance applications. You should have deep expertise in one or more programming languages, strong proficiency in relevant frameworks and libraries, and a solid understanding of software design principles, performance optimization, and best practices.

As a detail-oriented and adaptable individual, you will thrive in a fast-paced work environment and possess strong logical reasoning skills. Experience integrating analytics, monitoring, and security best practices relevant to your technical domain is a plus. Containerization technologies, such as Docker, and knowledge of complementary technologies, such as backend systems, APIs, databases, and authentication, are also desirable.

This role may be offered as a full-time, part-time, or contractor position, depending on role needs and candidate fit. As a contractor, you will have the flexibility to set your own hours and determine the exact amount of time needed to complete deliverables. You will be working remotely from any location worldwide, subject to legal eligibility, time-zone compatibility, and role-specific needs.

US-based candidates will be compensated between $60/hour and $100/hour, depending on factors including relevant experience, skills, education, geographic location, and qualifications. International candidates will receive information during the recruitment process.

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In this role, you will contribute high-quality accounting analysis, explanations, and evaluations that support the training of AI models on complex accounting concepts.

Working in close collaboration with technical and research teams, you will help shape new AI capabilities by evaluating sophisticated accounting scenarios and guiding how models reason through them.

You will draw on deep knowledge of financial reporting, consolidations, internal controls, and U.S. GAAP to identify and analyze challenging accounting problems comparable to upper-division or graduate-level coursework.

Your input will directly influence how effectively AI systems interpret accounting standards and communicate sound accounting judgments.

This role is well suited for faculty who thrive in intellectually dynamic environments and are comfortable engaging with evolving prompts, frameworks, and research objectives.

Responsibilities:

• Use proprietary software applications to provide input/labels on defined projects.
• Support and ensure the delivery of high-quality curated data.
• Play a pivotal role in supporting and contributing to the training of new tasks, working closely with the technical staff to ensure the successful development and implementation of cutting-edge initiatives/technologies.
• Interact with the technical staff to help improve the design of efficient annotation tools.
• Choose problems from corporate accounting fields that align with your expertise, providing rigorous solutions and model critiques where you can confidently provide detailed solutions and evaluate model responses.
• Regularly interpret, analyze, and execute tasks based on given instructions.

Basic Qualifications:

• PhD or DBA in Accounting, or a Master’s degree in Accounting combined with a CPA license and substantial professional experience.
• Ability to analyze and explain complex GAAP issues clearly and rigorously, consistent with upper-division or graduate-level instruction.
• Strong written communication skills in English, with the ability to articulate accounting judgments in both formal, technical contexts and instructional explanations.
• Familiarity with authoritative accounting and financial reporting resources, such as FASB Codification, SEC EDGAR, and public-company financial statements.
• Excellent analytical judgment, intellectual curiosity, and capacity to reason independently in situations involving ambiguity or incomplete information.
• Demonstrated interest in emerging technologies and innovation in accounting education, research, or practice.

Preferred Skills and Experience:

• Demonstrated expertise in corporate financial accounting and reporting, grounded in professional practice within public accounting or SEC-reporting organizations, with experience addressing complex transactions, consolidations, or judgment-intensive accounting matters.
• Experience authoring or reviewing technical accounting analyses, including research memoranda, disclosure analyses, or case-based materials.
• Peer-reviewed publication(s) in academic or practitioner-oriented accounting journals, or comparable scholarly output.
• Teaching experience at the undergraduate or graduate level in financial accounting, intermediate/advanced accounting, auditing, or related subjects.

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.
• 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 we are unable to hire in the states of 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, Mac with MacOS 11.0 or later, or Windows 10 or later.

Compensation and Benefits:

US based candidates: $45/hour - $100/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. xAI is an equal opportunity employer. For details on data processing, view our Recruitment Privacy Notice.

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To be successful in this role, you will need expertise in improving Large Language Models (LLMs), specifically related to CSE, to maximize efficiencies in enforcement and support. You will also need to have a proven expertise in identifying, mitigating, and preventing Child Sexual Abuse Material (CSAM) and Child Sexual Exploitation (CSE), including grooming behaviors and risks in AI-generated content, with strong knowledge of relevant legal obligations (such as NCMEC reporting) and industry standards for protecting minors.

You will also have experience in online safety and reducing harm to protect our users and preserve Free Speech in the global public square. You will be able to interpret and apply xAI safety policies effectively, and have strong skills in ethical reasoning and risk assessment. You will also have a strong ability to utilize resources, guidelines, and frameworks for accurate safety-focused actions and escalations.

In addition, you will have strong communication, interpersonal, analytical, and ethical decision-making skills. You will be committed to continuous improvement of processes to prioritize safety and risk mitigation. You will also have expertise in data analysis to identify emerging abuse vectors, uncover opportunities for operational efficiencies, and design automations that strengthen enforcement effectiveness and platform safety.

Preferred qualifications include experience working in a Trust and Safety for a social media company, leveraging AI or other automation tools. You will also have experience collaborating with child safety organizations (such as NCMEC) and utilizing specialized detection tools or developing classifiers for CSAM/CSE in social media or generative AI platforms. Additionally, you will have expertise in red-teaming and adversarial testing of Large Language Models to proactively identify novel abuse vectors, jailbreaks, and safety failure modes, with a proven ability to translate findings into concrete improvements for enforcement systems and platform robustness.

This role may involve exposure to sensitive or graphic content, including vulgar language, violent threats, pornography, and other graphic images.

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xAI is seeking a Senior Analyst - Safety Operations (CSE) to join our team. As a Senior Analyst, you will play a critical role in ensuring the safety and integrity of our AI systems.

Responsibilities

• Process appeals, audit automations, and properly label use cases in the system.
• Provide labels, annotations, and inputs on projects involving safety protocols, risk scenarios, and policy compliance.
• Support the delivery of high-quality curated data that reinforces xAI's rules and ethical alignment.
• Collaborate with team members to provide feedback on tasks that improve AI's defenses to detect illegal and unethical behavior, as well as align Grok with our rules enforcement.

Basic Qualifications

• Expertise in improving Large Language Models (LLMs), specifically related to CSE, to maximize efficiencies in enforcement and support and ability to propose solutions to increase security and safety of our platform.
• Proven expertise in identifying, mitigating, and preventing Child Sexual Abuse Material (CSAM) and Child Sexual Exploitation (CSE), including grooming behaviors and risks in AI-generated content, with strong knowledge of relevant legal obligations (such as NCMEC reporting) and industry standards for protecting minors.
• Proven experience in online safety and reducing harm to protect our users and preserve Free Speech in the global public square.
• Ability to interpret and apply xAI safety policies effectively.
• Proficiency in analyzing complex scenarios, with strong skills in ethical reasoning and risk assessment.
• Strong ability to utilize resources, guidelines, and frameworks for accurate safety-focused actions and escalations.
• Strong communication, interpersonal, analytical, and ethical decision-making skills.
• Commitment to continuous improvement of processes to prioritize safety and risk mitigation.
• Expertise in data analysis to identify emerging abuse vectors, uncover opportunities for operational efficiencies, and design automations that strengthen enforcement effectiveness and platform safety.

Preferred Skills and Experience

• Experience working in a Trust and Safety for a social media company, leveraging AI or other automation tools.
• Experience collaborating with child safety organizations (such as NCMEC) and utilizing specialized detection tools or developing classifiers for CSAM/CSE in social media or generative AI platforms.
• Expertise in red-teaming and adversarial testing of Large Language Models to proactively identify novel abuse vectors, jailbreaks, and safety failure modes, with a proven ability to translate findings into concrete improvements for enforcement systems and platform robustness.

This role may involve exposure to sensitive or graphic content, including vulgar language, violent threats, pornography, and other graphic images.

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xAI's mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge.

RESPONSIBILITIES:

• Process appeals, audit automations, and label use cases in the system.

• Provide labels, annotations, and inputs on projects involving safety protocols, risk scenarios, and policy compliance.

• Support the delivery of high-quality curated data that reinforces xAI's rules and ethical alignment.

• Collaborate with team members to provide feedback on tasks that improve AI's defenses to detect illegal and unethical behaviour, as well as align Grok with our rules enforcement.

BASIC QUALIFICATIONS:

• Expertise in improving Large Language Models (LLMs) to maximise efficiencies in enforcement and support and ability to propose solutions to increase security and safety of our platform.

• Proven experience in online safety and reducing harm to protect our users and preserve Free Speech in the global public square.

• Ability to interpret and apply xAI safety policies effectively.

• Proficiency in analysing complex scenarios, with strong skills in ethical reasoning and risk assessment.

• Strong ability to utilise resources, guidelines, and frameworks for accurate safety-focused actions and escalations.

• Strong communication, interpersonal, analytical, and ethical decision-making skills.

• Commitment to continuous improvement of processes to prioritise safety and risk mitigation.

• Expertise in data analysis to identify emerging abuse vectors, uncover opportunities for operational efficiencies, and design automations that strengthen enforcement effectiveness and platform safety.

PREFERRED SKILLS AND EXPERIENCE:

• Experience working in a Trust and Safety for a social media company, leveraging AI or other automation tools.

• Expertise in red-teaming and adversarial testing of Large Language Models to proactively identify novel abuse vectors, jailbreaks, and safety failure modes, with a proven ability to translate findings into concrete improvements for enforcement systems and platform robustness.

This role may involve exposure to sensitive or graphic content, including vulgar language, violent threats, pornography, and other graphic images.

COMPENSATION AND BENEFITS:

Base salary is just one part of our total rewards package at xAI, which also 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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You will join the multimodal team to push toward superhuman multimodal intelligence. Advance understanding and generation across modalities,image, video, audio, and text,spanning the full stack: data curation/acquisition, tokenizer training, large-scale pre-training, post-training/alignment, infrastructure/scaling, evaluation, tooling/demos, and end-to-end product experiences.

Collaborate cross-functionally with pre-training, post-training, reasoning, data, applied, and product teams to deliver frontier capabilities in multimodal reasoning, world modeling, tool use, agentic behaviors, and interactive human-AI collaboration. Contribute to building models that can see, hear, reason about, and interact with the world in real time at unprecedented levels.

Responsibilities

• Design, build, and optimize large-scale distributed systems for multimodal pre-training, post-training, inference, data processing, and tokenization at web/petabyte scale.
• Develop high-throughput pipelines for data acquisition, preprocessing, filtering, generation, decoding, loading, crawling, visualization, and management (images, videos, audio + text).
• Advance multimodal capabilities including spatial-temporal compression, cross-modal alignment, world modeling, reasoning, emergent abilities, audio/image/video understanding & generation, real-time video processing, and noisy data handling.
• Drive data quality and studies: curation (human/synthetic), filtering techniques, analysis, and scalable pipelines to support trillion-parameter models.
• Create evaluation frameworks, internal benchmarks, reward models, and metrics that capture real-world usage, failure modes, interactive dynamics, and human-AI synergy.
• Innovate on algorithms, modeling approaches, hardware/software/algorithm co-design, and scaling paradigms for state-of-the-art performance.
• Build research tooling, user-friendly interfaces, prototypes/demos, full-stack applications, and enable rapid iteration based on feedback.
• Work across the stack (pre-training → SFT/RL/post-training) to enable reasoning, tool calling, agentic behaviors, orchestration, and seamless real-time interactions.

Basic Qualifications

• Hands-on experience with multimodal pre-training, post-training, or fine-tuning (vision, audio, video, or cross-modal).
• Expert-level proficiency in Python (core language), with strong experience in at least one of: JAX / PyTorch / XLA.
• Proven track record building or optimizing large-scale distributed ML systems (training/inference optimization, GPU utilization, multi-GPU/TPU setups, hardware co-design).
• Deep experience designing and running data pipelines at scale: curation, filtering, generation, quality studies, especially for noisy/real-world multimodal data.
• Strong fundamentals in evaluation design, benchmarks, reward modeling, or RL techniques (particularly for interactive/agentic behaviors).
• Proactive self-starter who thrives in high-intensity environments and is passionate about pushing multimodal AI frontiers.
• Willingness to own end-to-end initiatives and do whatever it takes to deliver breakthrough user experiences.

Preferred Skills and Experience

• Experience leading major improvements in model capabilities through better data, modeling, algorithms, or scaling.
• Familiarity with state-of-the-art in multimodal LLMs, scaling laws, tokenizers, compression techniques, reasoning, or agentic systems.
• Proficiency in Rust and/or C++ for performance-critical components.
• Hands-on work with large-scale orchestration tools such as Spark, Ray, or Kubernetes.
• Background building full-stack tooling: performant interfaces, real-time research demos/apps, or end-to-end product ownership.
• Passion for end-to-end user experience in interactive, real-time multimodal AI systems.

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As a Thermal Engineer at Shield AI, you will:

• Own thermal analysis and design efforts for unmanned aerial vehicle avionics, including custom power electronics
• Develop and validate analytical, numerical, and computational models for heat transfer and fluid flow using hand calculations and CFD tools such as FloEFD
• Provide input to trade studies, system architecture decisions, and risk assessments
• Assist cross-functional teams designing power electronic circuits and environmental enclosures
• Contribute to design requirements that impact circuit part selection, board layout, material selection, and other design aspects
• Drive test planning, instrumentation, and data analysis to correlate models with experimental results
• Communicate technical findings clearly through executive-level briefings, design reviews, and written reports

Required qualifications:

• B.S. in Mechanical Engineering, Aerospace Engineering, or related discipline
• Internship or engineering club experience in avionics or electronics thermal engineering
• Knowledge of heat transfer (conduction, convection, radiation) and fluid mechanics
• Familiarity with thermal analysis and CFD tools (e.g., ANSYS Icepak, FloEFD, STAR-CCM+)
• Experience with CAD design tools such as NX, SolidWorks, or similar
• Demonstrated experience applying first-principles reasoning to engineering problems
• Strong written and verbal communication skills, with a track record of leading technical discussions and presenting to stakeholders

Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location.

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As a Staff Thermal Engineer, you will contribute to thermal analysis and design efforts for unmanned aerial vehicle avionics and thermal/fluid systems. You will develop and validate analytical, numerical, and computational models for heat transfer and fluid flow using hand calculations and CFD tools such as FloEFD. You will drive test planning, instrumentation, and data analysis to correlate models with experimental results.

Key responsibilities include:

• Contributing to thermal analysis and design efforts for unmanned aerial vehicle avionics and thermal/fluid systems
• Developing and validating analytical, numerical, and computational models for heat transfer and fluid flow using hand calculations and CFD tools such as FloEFD
• Driving test planning, instrumentation, and data analysis to correlate models with experimental results
• Communicating technical findings clearly through executive-level briefings, design reviews, and written reports

Requirements include:

• B.S. in Mechanical Engineering, Aerospace Engineering, or related discipline
• Minimum 7 years of professional experience in avionics or electronics thermal engineering
• Strong expertise in heat transfer (conduction, convection, radiation) and fluid mechanics
• Deep understanding of active and passive cooling solutions and their integration at component and system level
• Proficiency with thermal analysis and CFD tools (e.g., ANSYS Icepak, FloEFD, STAR-CCM+)
• Proficiency with CAD design tools such as NX, SolidWorks, or similar
• Demonstrated experience applying first-principles reasoning to complex engineering problems
• Strong written and verbal communication skills, with a track record of leading technical discussions and presenting to stakeholders

Preferred qualifications include:

• M.S. or Ph.D. in a relevant engineering discipline
• Experience with high-altitude aircraft avionics cooling and thermal design
• Familiarity with aircraft integration constraints (power, weight, volume, maintainability, safety)
• Hands-on experience with thermal and fluid system testing, instrumentation, and validation
• Knowledge of materials and manufacturing methods relevant to thermal management (pumps, heat exchangers, composites, etc.)
• Experience guiding trade studies, proposals, and customer interactions in aerospace or defense programs
• Background in multi-disciplinary system integration, spanning avionics, fluid systems, and systems engineering

Salary: $136,730 - $205,096 a year

Benefits: Pay within range listed + Bonus + Benefits + Equity

Note: Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location.

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This role is best suited for an engineer who thrives on first-principles problem solving, is comfortable with ambiguous, open-ended challenges, and can bridge technical disciplines with strong communication and collaboration skills and the ability to simplify and communicate complex problems.

The engineer will be a key contributor in shaping designs, mentoring peers, and ensuring robust thermal solutions that meet mission-critical aerospace requirements.

Responsibilities:

• Own thermal analysis and design efforts for unmanned aerial vehicle avionics including custom power electronics
• Develop and validate analytical, numerical, and computational models for heat transfer and fluid flow using hand calculations and CFD tools such as FloEFD
• Provide technical leadership in trade studies, system architecture decisions, and risk assessments
• Lead cross-functional teams designing power electronic circuits and environmental enclosures. Provide design requirements that impact circuit part selection, board layout, material selection, and other design aspects
• Drive test planning, instrumentation, and data analysis to correlate models with experimental results
• Mentor junior engineers and guide cross-disciplinary teams in applying thermal/fluid fundamentals
• Communicate technical findings clearly through executive-level briefings, design reviews, and written reports
• Proactively identify risks, propose solutions, and influence electrical and/or PCBA design direction

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As the Principal Aircraft Thermal Engineer, you will lead thermal analysis and characterization efforts for unmanned aerial vehicle aircraft-level thermal systems. You will architect and validate analytical, numerical, and computational models for heat transfer and fluid flow using hand calculations, finite difference methods, and CFD tools such as FloEFD.

You will provide leadership in trade studies, system architecture decisions, requirements generation, and technical risk assessments. You will define and oversee test planning, instrumentation, and data analysis to correlate models with experimental results.

You will mentor and guide cross-disciplinary teams in applying thermal/fluid fundamentals. You will communicate technical findings through executive-level briefings, design reviews, and technical reports.

Key responsibilities include:

• Leading thermal analysis and characterization efforts for unmanned aerial vehicle aircraft-level thermal systems
• Architecting and validating analytical, numerical, and computational models for heat transfer and fluid flow
• Providing leadership in trade studies, system architecture decisions, requirements generation, and technical risk assessments
• Defining and overseeing test planning, instrumentation, and data analysis
• Mentoring and guiding cross-disciplinary teams
• Communicating technical findings through executive-level briefings, design reviews, and technical reports

Requirements include:

• B.S. in Mechanical Engineering, Aerospace Engineering, or related discipline
• Minimum 12 years of professional experience in avionics or electronics thermal engineering
• Deep expertise in heat transfer (conduction, convection, radiation) and fluid mechanics
• Advanced understanding of active and passive cooling solutions and their integration at the component and system level
• Proficiency with thermal analysis and CFD tools (e.g., FloEFD, STAR-CCM+)
• Proficiency with CAD design tools such as NX, SolidWorks, or similar
• Demonstrated ability to apply first-principles reasoning to complex engineering problems
• Ability to learn new and cutting-edge materials knowledge and thermal management techniques from a variety of sources (technical papers, text books, etc.) and apply it to the development of advanced thermal management design
• Strong communication and leadership skills, with experience presenting to executives and customers

Preferred qualifications include:

• M.S. or Ph.D. in a relevant engineering discipline
• Extensive experience with high-altitude aircraft thermal management, analysis, and design
• Familiarity with aircraft integration constraints (power, weight, volume, maintainability, safety)
• Hands-on experience with thermal and fluid system testing, instrumentation, and validation
• Knowledge of materials and manufacturing methods relevant to aerospace thermal management
• Experience guiding trade studies, proposals, and customer interactions in aerospace or defense programs
• Background in multi-disciplinary system integration, spanning avionics, fluid systems, and systems engineering

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At Mistral, we are on a mission to democratize AI, producing frontier intelligence for everyone, developed in the open, and built by engineers all over the world.

We develop models for the enterprise and for consumers, focusing on delivering systems which can really change the way in which businesses operate and which can integrate into our daily lives. All while releasing frontier models open-source, for everyone to try and benefit.

Job Description

We are hiring experts in the training of large language models and distributed systems. Join us to be part of a pioneering company shaping the future of AI.

Responsibilities

• Research and develop novel AI methods for general-purpose mobile manipulation robots
• Build tooling and infrastructure to allow training, evaluation and analysis of AI models at scale
• Work cross-functionally with other scientists, engineers and product teams to deploy AI systems on real robot platforms

About You

• You have hands-on experience either building and deploying AI systems on physical robots or developing large vision-language models
• You are a highly proficient software engineer in at least one programming language (preferably Python)
• You have hands-on experience with AI frameworks (preferably PyTorch)
• You have high engineering competence. This means being able to design complex software and make it usable in production
• You are a self-starter, autonomous and a team player

Nice to Have

• You have experience in one or more of the following: navigation, manipulation, simulators, 3D, embodied reasoning or vision-language-action models
• You can navigate the full MLOps stack, for instance, fine-tuning, evaluation and deployment
• You have a strong publication record in a relevant scientific domain

Benefits

In France:

• Competitive cash salary and equity
• Food: Daily lunch vouchers
• Sport: Monthly contribution to a Gympass subscription
• Transportation: Monthly contribution to a mobility pass
• Health: Full health insurance for you and your family
• Parental: Generous parental leave policy
• Visa sponsorship

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Your responsibilities will include: Assisting patients with menu selections, when needed, as part of AYS assuring compliance with physician prescribed MNT, according to the individualised needs of the patient with full consideration of patient safety. Maintaining patient database utilising Epic and Computrition by correctly inputting physician MNT orders, patient allergy information, and patient special services such as appropriateness to order through the AYS system. Answering the telephone, taking messages and relaying information as needed. This includes answering the patient menu line. Providing troubleshooting of patient meal problems to include referring patients in need of assistance to a registered dietitian. Maintaining accurate reports such as patients not appropriate to order (NAPS), patients who have missed 2 meals, required meal counts, etc. Ensuring correct menu item selection for MNT on AYS orders according the individualised need of the patient. Conducting Performance Improvement monitoring, measuring, and tracking results using specified indicators. Properly preparing patient nourishments and enteral nutrition products according to HACCP guidelines. Stocking office supplies, as needed, and maintaining organisation of work area.

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As a R&D Staff Engineer, you will research, design, and implement algorithms for 3D geometry processing and mesh generation incorporating AI/ML to increase automation and robustness.

Your expertise in AI/ML applications for 3D geometry processing, proficient software development skills, especially with Python and C/C++, and solid understanding of geometry processing, mesh generation, and numerical methods are essential.

You will collaborate closely with the meshing software development team to plan, create, and evolve simulation software capabilities.

Your strong analytical skills and ability to overcome obstacles make you a natural fit for an innovative team by pushing the boundaries of simulation technology.

You will accelerate the adoption of AI/ML technologies within simulation software, making model creation faster and more accessible.

You will enable engineers and researchers to solve complex geometric and numerical problems more efficiently.

You will improve the accuracy and performance of simulation models through advanced mesh generation techniques.

You will drive innovation in the field of computational geometry and simulation technology.

You will contribute to the development of robust, scalable software solutions used by leading companies worldwide.

You will help Synopsys maintain its leadership in high-performance simulation and design automation tools.

The base salary range for this role is $120,000-$180,000.

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Key responsibilities include:

• Post-training/instruction tuning state-of-the-art language models, focusing on text-to-text, image/video/audio-to-text modalities and agentic capabilities
• Exploring data, reasoning, and algorithmic solutions to ensure Gemini models are safe and work for everyone
• Improving Gemini's adversarial robustness, with a focus on high-stakes abuse risks
• Designing and maintaining high-quality evaluation protocols to assess model behaviour gaps and headroom related to safety and fairness
• Developing and executing experimental plans to address known gaps or construct entirely new capabilities

To succeed in this role, you should have a PhD in Computer Science or a related field, significant LLM post-training experience, and a track record of publications at top conferences. Experience in reward modelling and reinforcement learning for LLMs instruction tuning, long-range reinforcement learning, safety, fairness, and alignment is an advantage.

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Your main responsibilities will include:

• Curating and maintaining Spotify editorial playlists, including hits, genre-specific, and mood/activity playlists
• Developing and co-creating editorial strategies for Türkiye
• Analyzing platform data to refine and improve playlist programming and overall editorial performance
• Staying deeply connected to the Turkish music landscape, identifying new talent and emerging trends
• Translating music and cultural knowledge into engaging, relevant content for Spotify users

You'll be a key player in developing our editorial strategy for Türkiye, working closely with internal teams to ensure editorial decisions align with broader business and creative objectives.

To succeed in this role, you'll need to have a deep understanding of the Turkish music ecosystem, from mainstream to underground movements, and an instinctive sense of what music fits different moments, moods, and cultural contexts. You'll also need to be able to communicate effectively with internal teams and stakeholders, and be comfortable leveraging data to inform decision-making.

If you're passionate about music and have a deep understanding of the Turkish music landscape, we'd love to hear from you.

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We're a team of scientists, engineers, machine learning experts, and more, working together to advance the state of the art in artificial intelligence.

About Us The Agentic Red Team is a specialized, high-velocity unit within Google DeepMind Security. Our mission is to close the 'Agentic Launch Gap',the critical window where novel AI capabilities outpace traditional security reviews.

The Role As a Senior Security Engineer on the Agentic Red Team, you will be the primary technical executor of our adversarial engagements. You will work 'in the room' with product builders, identifying architectural flaws during the design phase long before formal reviews begin.

Key Responsibilities:

• Execute Agile Red Teaming: Conduct rapid, high-impact security assessments on agentic services, focusing on vulnerabilities unique to GenAI such as prompt injection, tool-use escalation, and autonomous lateral movement.
• Develop Advanced Exploits: Engineer and execute complex attack sequences that exploit non-deterministic model behaviors, agentic logic errors, and data poisoning vectors.
• Build Automated Defenses: Write code to transform manual vulnerability discoveries into automated regression testing frameworks ('Auto Red Teaming') that prevent regression in future model versions.
• Embed with Product Teams: Partner directly with developers during the design and build phases to provide immediate feedback, effectively shortening the feedback loop between offensive findings and defensive engineering.
• Curate Threat Intelligence: Maintain and expand a library of agent-specific attack patterns and exploit primitives to establish robust release criteria for new models.

About You In order to set you up for success as a Software Engineer at Google DeepMind, we look for the following skills and experience:

• Bachelor's degree in Computer Science, Information Security, or equivalent practical experience.
• Experience in Red Teaming, Offensive Security, or Adversarial Machine Learning.
• Strong coding skills in Python, Go, or C++ with experience building security tools or automation.
• Technical understanding of LLM architectures, agentic workflows (e.g., chain-of-thought reasoning), and common AI vulnerability classes.

Preferred Qualifications

• Hands-on experience developing exploits for GenAI models (e.g., prompt injection, adversarial examples, training data extraction).
• Experience working in a consulting capacity with product teams or in a fast-paced 'startup-like' environment.
• Familiarity with AI safety benchmarks, evaluation frameworks, and fuzzing techniques.
• Ability to translate complex probabilistic risks into actionable engineering fixes for developers.

Salary & Benefits The US base salary range for this full-time position is between $166,000 - $244,000 + bonus + equity + benefits.

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We are hiring experts in the training of large language models and distributed systems to join our research team.

Key responsibilities:

• Research and develop novel AI methods for general-purpose mobile manipulation robots
• Build tooling and infrastructure to allow training, evaluation and analysis of AI models at scale
• Work cross-functionally with other scientists, engineers and product teams to deploy AI systems on real robot platforms

About you

• You have hands-on experience either building and deploying AI systems on physical robots or developing large vision-language models
• You are a highly proficient software engineer in at least one programming language (preferably Python)
• You have hands-on experience with AI frameworks (preferably PyTorch)
• You have high engineering competence. This means being able to design complex software and make it usable in production

Ideal candidates will have experience in one or more of the following:

• Navigation, manipulation, simulators, 3D, embodied reasoning or vision-language-action models
• The full MLOps stack, for instance, fine-tuning, evaluation and deployment

Benefits in France

• Competitive cash salary and equity
• Food: Daily lunch vouchers
• Sport: Monthly contribution to a Gympass subscription
• Transportation: Monthly contribution to a mobility pass
• Health: Full health insurance for you and your family
• Parental: Generous parental leave policy
• Visa sponsorship

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We work on the bleeding edge and leverage the most powerful pretrained models and algorithms, making it critical that we ensure our AI systems behave safely and align with organisational values.

You will be responsible for designing novel safety evaluation frameworks, curating high-quality data for robust evaluations and training, prototyping new safety capabilities, and developing safety-focused fine-tuning algorithms.

We’re looking for outstanding individuals with deep expertise in AI safety who can translate research insights into practical solutions while being a strong communicator and collaborative teammate.

The ideal candidate takes the initiative in exploring new safety methodologies and enjoys building world-class, trustworthy AI experiences in a fast-paced applied research environment.

Microsoft’s mission is to empower every person and every organisation on the planet to achieve more.

As employees we come together with a growth mindset, innovate to empower others, and collaborate to realise our shared goals.

Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Starting January 26, 2026, MAI employees are expected to work from a designated Microsoft office at least four days a week if they live within 50 miles (U.S.) or 25 miles (non-U.S., country-specific) of that location.

This expectation is subject to local law and may vary by jurisdiction.

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We work on the bleeding edge and leverage the most powerful pretrained models and algorithms, making it critical that we ensure our AI systems behave safely and align with organisational values.

You will be responsible for designing novel safety evaluation frameworks, curating high-quality data for robust evaluations and training, prototyping new safety capabilities, and developing safety-focused fine-tuning algorithms.

We’re looking for outstanding individuals with deep expertise in AI safety who can translate research insights into practical solutions while being a strong communicator and collaborative teammate.

The ideal candidate takes the initiative in exploring new safety methodologies and enjoys building world-class, trustworthy AI experiences in a fast-paced applied research environment.

Responsibilities:

Leverage expertise in AI safety to uncover potential risks and develop novel mitigation strategies, including alignment techniques, constitutional AI approaches, RLHF, and robustness improvements for large language models.

Create and implement comprehensive evaluation frameworks and red-teaming methodologies to assess model safety across diverse scenarios, edge cases, and potential failure modes.

Build automated safety testing systems, generalise safety solutions into repeatable frameworks, and write efficient code for safety model pipelines and intervention systems.

Maintain a user-oriented perspective by understanding safety needs from user perspectives, validating safety approaches through user research, and serving as a trusted advisor on AI safety matters.

Track advances in AI safety research, identify relevant state-of-the-art techniques, and adapt safety algorithms to drive innovation in production systems serving millions of users.

Embody our culture and values.

Qualifications:

Required Qualifications:

Bachelor’s Degree in Computer Science, or related technical discipline AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.

Preferred Qualifications:

Bachelor’s Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR Master’s Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.

Experience prompting and working with large language models.

Experience writing production-quality Python code.

Demonstrated interest in Responsible AI.

Software Engineering IC4 – The typical base pay range for this role across the U.S. is USD $119,800 – $234,700 per year.

Software Engineering IC5 – The typical base pay range for this role across the U.S. is USD $139,900 – $274,800 per year.

This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.

Microsoft is an equal opportunity employer.

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We work on the bleeding edge and leverage the most powerful pretrained models and algorithms, making it critical that we ensure our AI systems behave safely and align with organisational values.

You will be responsible for designing novel safety evaluation frameworks, curating high-quality data for robust evaluations and training, prototyping new safety capabilities, and developing safety-focused fine-tuning algorithms.

We’re looking for outstanding individuals with deep expertise in AI safety who can translate research insights into practical solutions while being a strong communicator and collaborative teammate.

The ideal candidate takes the initiative in exploring new safety methodologies and enjoys building world-class, trustworthy AI experiences in a fast-paced applied research environment.

Microsoft’s mission is to empower every person and every organisation on the planet to achieve more.

As employees we come together with a growth mindset, innovate to empower others, and collaborate to realise our shared goals.

Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Starting January 26, 2026, MAI employees are expected to work from a designated Microsoft office at least four days a week if they live within 50 miles (U.S.) or 25 miles (non-U.S., country-specific) of that location.

This expectation is subject to local law and may vary by jurisdiction.

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Model Policy Manager, Youth Well-being

Location

San Francisco

Employment Type

Full time

Department

Safety Systems

Compensation

• Estimated Base Salary $207K – $295K • Offers Equity

The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.

• Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts

• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)

• 401(k) retirement plan with employer match

• Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)

• Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees

• 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)

• Mental health and wellness support

• Employer-paid basic life and disability coverage

• Annual learning and development stipend to fuel your professional growth

• Daily meals in our offices, and meal delivery credits as eligible

• Relocation support for eligible employees

• Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

More details about our benefits are available to candidates during the hiring process.

This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.

About the Team

The Safety Systems team is at the forefront of OpenAI's mission to build and deploy safe AGI, driving our commitment to AI safety and fostering a culture of trust and transparency.

The Model Policy team aligns model behavior with desired human values and norms. We co-design policy _with_ models and _for_ models by driving rapid policy taxonomy iteration based on data and defining evaluation criteria for foundational models’ ability to reason about safety. Key focus areas include: catastrophic risk, mental health, teen safety and multimodal safety.

About the Role

Providing access to powerful AI models introduces a host of challenging questions when it comes to model safety: How do we define safe behavior for how a model should behave? To what end? How do we do this in such a way that is actionable, objective and sustains replicability?

This is a senior role in which you’ll help shape policy creation and development at OpenAI and make an impact by helping ensure that our groundbreaking technologies do not create harm. The ideal candidate can identify and develop cohesive and thoughtful taxonomies of harm on high risk topics with a sense of urgency. They can balance internal and external input in making complex decisions, carefully think through trade-offs, and write principled, enforceable policies based on our values. Importantly, this role is embedded in our research teams and directly informs model training.

This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.

In this role, you’ll:

• Design model policies that govern safe model behavior in an objective and defensible way - e.g. how should the model respond in risky/unsafe scenarios? What does unsafe mean? How do we achieve safety while preserving beneficial model capabilities?

• You will develop taxonomies that inform data collection campaigns, model behaviour and monitoring strategies and also toe the line between maximizing utility and preventing catastrophic risk.

• Lead prioritization for safety efforts across the company for new model launches, understanding and addressing technical and business trade-offs.

• Develop a broad range of subject matter expertise while maintaining agility across topics.

• You will work across many internal teams which will require high organizational acumen and confident decision making.

You might thrive in this role if you:

• Have extensive experience researching LLMs, ML, AI, tech policy, moral reasoning, and/or enjoy classification problems.

• Have extensive experience defining, refining and enforcing policies for ML models across training, evaluation, and deployment.

• Understand the practical challenges of translating policy into model behavior across the full training stack, and can incorporate these constraints into policy design.

• Can reason about the benefits and risks of open-ended problem spaces, generate novel approaches under ambiguity, and take full ownership of end-to-end solutions from concept through execution.

Most relevant publications:

• Introducing HealthBench

• Preparing for future AI capabilities in biology

• Safety evaluations hub

• OpenAI GPT5 System Card

• Evaluating Fairness in ChatGPT

• Improving Model Safety Behavior with Rule-Based Rewards

• OpenAI Model Spec

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences of individuals from all walks of life.

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San Francisco

Employment Type

Full time

Department

Safety Systems

Compensation

• Estimated Base Salary $207K – $295K • Offers Equity

The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.

• Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts

• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)

• 401(k) retirement plan with employer match

• Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)

• Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees

• 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)

• Mental health and wellness support

• Employer-paid basic life and disability coverage

• Annual learning and development stipend to fuel your professional growth

• Daily meals in our offices, and meal delivery credits as eligible

• Relocation support for eligible employees

• Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

More details about our benefits are available to candidates during the hiring process.

This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.

About the Team

The Safety Systems team is at the forefront of OpenAI's mission to build and deploy safe AGI, driving our commitment to AI safety and fostering a culture of trust and transparency.

The Model Policy team aligns model behavior with desired human values and norms. We co-design policy _with_ models and _for_ models by driving rapid policy taxonomy iteration based on data and defining evaluation criteria for foundational models’ ability to reason about safety. Key focus areas include: catastrophic risk, mental health, teen safety and multimodal safety.

About the Role

Providing access to frontier AI systems raises complex questions around dual-use science and catastrophic risk. How should models respond to requests involving chemical synthesis, biological experimentation, or pathogen research? Where is the boundary between legitimate scientific inquiry and information that could enable misuse? How do we design policies that meaningfully reduce risk without unnecessarily restricting beneficial research?

This is a senior role in which you’ll help shape policy creation and development at OpenAI for addressing biological and chemical risks. You will develop structured policy frameworks and taxonomies to guide safe model behavior. This role sits at the intersection of biosecurity expertise, AI safety research, and policy design. You will help ensure that frontier AI systems can support beneficial life sciences research, such as drug discovery, public health, and biosafety, while reducing the risk that these capabilities could be misused.

This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.

In this role, you’ll:

• Design and maintain model policies governing chemical and biological risk, defining how models should safely handle dual-use scenarios.
• Develop structured taxonomies of chemical and biological risk that inform model training data, evaluation benchmarks, and safety monitoring systems.
• Translate biosecurity and chemical security expertise into actionable model behavior, working closely with research and engineering teams to operationalize policy in training and evaluation pipelines.
• Develop a broad range of subject matter expertise while maintaining agility across topics.
• Identify emerging risk vectors where frontier AI capabilities could meaningfully lower barriers to harmful activity and develop mitigation strategies.
• Engage with internal and external subject-matter experts in biosecurity, biodefense, and chemical safety to ensure policies reflect real-world risk landscapes.

You might thrive in this role if you:

• Have strong domain expertise in chemistry, biology, biosecurity, or related fields and are motivated to translate that expertise into principled, operational policies that scale to frontier AI systems.
• Have experience researching or working with LLMs, machine learning, AI governance, technology policy, or related areas, and enjoy tackling structured reasoning and classification problems—such as defining boundaries between legitimate scientific inquiry and potentially harmful applications.
• Have experience designing, refining, or enforcing policies or safeguards for complex systems, whether in AI/ML environments, scientific research governance, national security contexts, or other high-stakes technical domains.
• Are comfortable navigating ambiguous, high-stakes problem spaces, balancing risk reduction with the benefits of scientific openness and innovation.
• Enjoy building new frameworks from first principles, reasoning about open-ended problems, and generating novel approaches under uncertainty. You take ownership of problems end-to-end—from defining the conceptual framework through collaborating with research and engineering teams

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Location

San Francisco

Employment Type

Full time

Department

Research

Compensation

• $380K – $445K • Offers Equity

The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.

• Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts

• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)

• 401(k) retirement plan with employer match

• Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)

• Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees

• 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)

• Mental health and wellness support

• Employer-paid basic life and disability coverage

• Annual learning and development stipend to fuel your professional growth

• Daily meals in our offices, and meal delivery credits as eligible

• Relocation support for eligible employees

• Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

More details about our benefits are available to candidates during the hiring process.

This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.

About the Team

The Codex team is responsible for building state-of-the-art AI systems that can write code, reason about software, and act as intelligent agents for developers and non-developers alike. Our mission is to push the frontier of code generation and agentic reasoning, and deploy these capabilities in real-world products such as ChatGPT and the API, as well as in next-generation tools specifically designed for agentic coding. We operate across research, engineering, product, and infrastructure—owning the full lifecycle of experimentation, deployment, and iteration on novel coding capabilities.

About the Role

As a member of the Codex team, you will advance the capabilities, performance, and reliability of AI coding models through a combination of research, experimentation, and system optimization. You’ll collaborate with world-class researchers and engineers to develop and deploy systems that help millions of users write better code, faster—while also ensuring these systems are efficient, cost-effective, and production-ready.

We’re looking for people who combine deep curiosity, strong technical fundamentals, and a bias toward impact. Whether your strengths lie in ML research, systems engineering, or performance optimization, you’ll play a pivotal role in pushing the state of the art and bringing these advances into the hands of real users.

This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.

In this role, you might:

• Design and run experiments to improve code generation, reasoning, and agentic behavior in Codex models.

• Develop research insights into model training, alignment, and evaluation.

• Hunt down and address inefficiencies across the Codex system stack—from agent behavior to LLM inference to container orchestration—and land high-leverage performance improvements.

• Build tooling to measure, profile, and optimize system performance at scale.

• Work across the stack to prototype new capabilities, debug complex issues, and ship improvements to production.

You might thrive in this role if you:

• Are excited to explore and push the boundaries of large language models, especially in the domain of software reasoning and code generation.

• Have strong software engineering skills and enjoy quickly turning ideas into working prototypes.

• Think holistically about performance, balancing speed, cost, and user experience.

• Bring creativity and rigor to open-ended research problems and thrive in highly iterative, ambiguous environments.

• Have experience operating across both ML systems and cloud infrastructure.

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.

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Researcher, Interpretability

Location

San Francisco

Employment Type

Full time

Location Type

Hybrid

Department

Safety Systems

Compensation

• $295K – $445K • Offers Equity

The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.

• Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts

• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)

• 401(k) retirement plan with employer match

• Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)

• Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees

• 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)

• Mental health and wellness support

• Employer-paid basic life and disability coverage

• Annual learning and development stipend to fuel your professional growth

• Daily meals in our offices, and meal delivery credits as eligible

• Relocation support for eligible employees

• Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

More details about our benefits are available to candidates during the hiring process.

This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.

About the Team

The Interpretability team studies internal representations of deep learning models. We are interested in using representations to understand model behavior, and in engineering models to have more understandable representations. We are particularly interested in applying our understanding to ensure the safety of powerful AI systems. Our working style is collaborative and curiosity-driven.

About the Role

OpenAI is seeking a researcher passionate about understanding deep networks, with a strong background in engineering, quantitative reasoning, and the research process. You will develop and carry out a research plan in mechanistic interpretability, in close collaboration with a highly motivated team. You will play a critical role in helping OpenAI ensure future models remain safe even as they grow in capability. This will make a significant impact on our goal of building and deploying safe AGI.

In this role, you will:

• Develop and publish research on techniques for understanding representations of deep networks.

• Engineer infrastructure for studying model internals at scale.

• Collaborate across teams to work on projects that OpenAI is uniquely suited to pursue.

• Guide research directions toward demonstrable usefulness and/or long-term scalability.

You might thrive in this role if you:

• Are excited about OpenAI’s mission of ensuring AGI benefits all of humanity, and are aligned with OpenAI’s charter.

• Show enthusiasm for long-term AI safety, and have thought deeply about technical paths to safe AGI.

• Bring experience in the field of AI safety, mechanistic interpretability, or spiritually related disciplines.

• Hold a Ph.D. or have research experience in computer science, machine learning, or a related field.

• Thrive in environments involving large-scale AI systems, and are excited to make use of OpenAI’s unique resources in this area.

• Possess 2+ years of research engineering experience and proficiency in Python or similar languages.

• Are deeply curious.

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.

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Researcher, Pretraining Safety

Location

San Francisco

Employment Type

Full time

Department

Safety Systems

Compensation

• $295K – $445K • Offers Equity

The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.

• Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts

• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)

• 401(k) retirement plan with employer match

• Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)

• Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees

• 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)

• Mental health and wellness support

• Employer-paid basic life and disability coverage

• Annual learning and development stipend to fuel your professional growth

• Daily meals in our offices, and meal delivery credits as eligible

• Relocation support for eligible employees

• Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

More details about our benefits are available to candidates during the hiring process.

This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.

About the Team

The Safety Systems team is responsible for various safety work to ensure our best models can be safely deployed to the real world to benefit the society and is at the forefront of OpenAI's mission to build and deploy safe AGI, driving our commitment to AI safety and fostering a culture of trust and transparency.

The Pretraining Safety team’s goal is to build safer, more capable base models and enable earlier, more reliable safety evaluation during training. We aim to:

1. Develop upstream safety evaluations that to monitor how and when unsafe behaviors and goals emerge;

1. Create safer priors through targeted pretraining and mid-training interventions that make downstream alignment more effective and efficient

1. Design safe-by-design architectures that allow for more controllability of model capabilities

In addition, we will conduct the foundational research necessary for understanding how behaviors emerge, generalize, and can be reliably measured throughout training.

About the Role

The Pretraining Safety team is pioneering how safety is built into models before they reach post-training and deployment. In this role, you will work throughout the full stack of model development with a focus on pre-training:

• Identify safety-relevant behaviors as they first emerge in base models

• Evaluate and reduce risk without waiting for full-scale training runs

• Design architectures and training setups that make safer behavior the default

• Strengthen models by incorporating richer, earlier safety signals

We collaborate across OpenAI’s safety ecosystem—from Safety Systems to Training—to ensure that safety foundations are robust, scalable, and grounded in real-world risks.

In this role, you will:

• Develop new techniques to predict, measure, and evaluate unsafe behavior in early-stage models

• Design data curation strategies that improve pretraining priors and reduce downstream risk

• Explore safe-by-design architectures and training configurations that improve controllability

• Introduce novel safety-oriented loss functions, metrics, and evals into the pretraining stack

• Work closely with cross-functional safety teams to unify pre- and post-training risk reduction

You might thrive in this role if you:

• Have experience developing or scaling pretraining architectures (LLMs, diffusion models, multimodal models, etc.)

• Are comfortable working with training infrastructure, data pipelines, and evaluation frameworks (e.g., Python, PyTorch/JAX, Apache Beam)

• Enjoy hands-on research — designing, implementing, and iterating on experiments

• Enjoy collaborating with diverse technical and cross-functional partners (e.g., policy, legal, training)

• Are data-driven with strong statistical reasoning and rigor in experimental design

• Value building clean, scalable research workflows and streamlining processes for yourself and others

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.

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Location

San Francisco

Employment Type

Full time

Department

Intelligence & Investigations

Compensation

• $230K – $325K • Offers Equity

The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.

Benefits

• Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts

• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)

• 401(k) retirement plan with employer match

• Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)

• Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees

• 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)

• Mental health and wellness support

• Employer-paid basic life and disability coverage

• Annual learning and development stipend to fuel your professional growth

• Daily meals in our offices, and meal delivery credits as eligible

• Relocation support for eligible employees

• Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

About the Team

The Intelligence and Investigations team seeks to rapidly identify and mitigate abuse and strategic risks to ensure a safe online ecosystem. We are dedicated to identifying emerging abuse trends, analyzing risks, and working with our internal and external partners to implement effective mitigation strategies to protect against misuse. Our efforts contribute to OpenAI's overarching goal of developing AI that benefits humanity.

About the Role

As a Data Scientist, you will lead econometric and experimental analysis to understand how risk changes in complex human–AI systems. Your work will focus on measuring the magnitude and impact of risk shifts in a fast-paced, rapidly evolving operational environment. You will design experiments and observational studies to identify causal drivers and analyze changes in risk across a wide range of surfaces and sources. Your analyses will directly inform prioritization and strategic risk management across the company.

In this role, you will:

• Own the design and execution of experimental and observational analyses used to assess strategic risk

• Develop econometric approaches to estimate the impact of product, policy, and external developments on key risk vectors

• Translate strategic risk questions into testable hypotheses and sound study designs

• Design and deploy A/B tests, as well as pseudo-experimental studies, to measure changes in risks and understand underlying mechanisms

• Identify, test, and explain product-driven, event-driven, or signal-driven changes in risk

• Establish baselines and statistical confidence around core metrics to size these problems

• Partner across teams to track strategic risks, identify opportunities for intervention, and develop analyses to evaluate those interventions

You might thrive in this role if you:

• Have 3–6+ years in econometrics, causal inference, or experimental research

• Are comfortable owning ambiguous analyses with large-scale influence

• Are strong in experimental design, observational methods, and statistical reasoning

• Write solid Python and SQL

• Experience delivering zero-to-one analyses and scaling them from concept through deployment

• Communicate data-driven findings clearly, including uncertainty and trade-offs, to non-technical partners and leadership

• Nice to have: experience in trust and safety, integrity, operational security, intelligence analysis or other quantitative risk-focused domains

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.

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What you'll do

Research & Development

• Post-train SOTA LLMs using the latest supervised and reinforcement learning techniques (SFT/DPO/GRPO)
• Leverage our rich query/answer dataset to scale model performance across Sonar, Deep Research, Comet, and Search products

What you need

• Proven experience with large-scale LLMs and Deep Learning systems

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What you'll do

• Work close with customers to understand new requests or customization feature from customer’s PRD/MRD
• Provide integration training to customers and conduct reviews on their major SoC milestones
• Provide feedback to Synopsys R&D for customization feature or continuous IIP product improvements
• Participate in IIP design reviews to align development with future customer needs
• Creativity and Innovation is highly inspired: such as developing small tools to simplify daily jobs or improving efficiency; authoring application notes for gate-level simulation, silicon debug and physical implementation.

What you need

• Bachelor’s and/or master’s degree in electrical and/or Electronic Engineering, Computer Engineering or Computer Science
• Minimum 5 years of Analog or Mixed signal IP or ASIC Design/Verification/Applications experience is required
• Hands-on experience on circuit design, RTL coding, simulation, synthesis, static timing check, equivalence check, etc.
• Domain knowledge PCI Express, CXL, Ethernet protocols
• Creative results are oriented with the ability to manage multiple tasks concurrently.
• Good verbal and written communication skills in English and ability to interact with customer
• High degree of self-motivation and personal responsibility
• Good inference, reasoning and problem-solving skills, and attention to details

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What you'll do

• Research and prototype machine learning and generative approaches for game content creation
• Work with development programmers and product programmers to deploy and productize novel technology results in Epic products

What you need

• PhD degree in Computer Science, Machine Learning, Mathematics, Programming, or a related discipline
• Proven applied research impact in shipping titles

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What you'll do

• Research and prototype machine learning and generative approaches for game content creation
• Work with development engineers and product engineers to deploy and productize novel technology results in Epic products

What you need

• PhD degree in Computer Science, Machine Learning, Mathematics, Engineering, or a related discipline
• Proven applied research impact in shipping titles

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What you'll do

The Research Programmer will be responsible for researching and prototyping machine learning and generative approaches for game content creation, working with development programmers and product programmers to deploy and productize novel technology results in Epic products, and engaging with the scientific community to contribute domain knowledge and advice in support of strategically relevant R&D efforts.

What you need

• PhD degree in Computer Science, Machine Learning, Mathematics, Programming, or a related discipline

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What you'll do

• Research and prototype machine learning and generative approaches for game content creation
• Work with development engineers and product engineers to deploy and productize novel technology results in Epic products

What you need

• PhD degree in Computer Science, Machine Learning, Mathematics, Engineering, or a related discipline
• Proven applied research impact in shipping titles

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What you'll do

The Facilities Equipment Service Coordinator is to organize and execute maintenance schedules, lead coordination among all internal teams, external vendors, spare parts and inventory management, and oversee implementation of the site preventive maintenance strategies.

• Responsibility 1: Work with other in-house departments (outside of facilities) on planned and unplanned activity requiring maintenance support related to facilities operations.
• Responsibility 2: Create requisitions to issue purchase orders for maintenance and repair of facilities equipment.
• Responsibility 3: Apply maintenance expertise in HDMA business planning operations.
• Responsibility 4: Support and coordinate operation of Facilities systems including, but not limited to, chillers, air compressors, HVAC, air house units, electrical distribution equipment, cafeteria equipment, meters, lighting, and controls.

What you need

• Required skill 1: High School Diploma
• Required skill 2: Ten (10) years minimum relevant working experience in Facilities Maintenance Field
• Required skill 3: Knowledge of: National Electrical Code (NFPA 70)

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