Your primary focus will be on designing, executing, and optimizing upstream Lentiviral Vector (LVV) processes with a primary focus on suspension bioreactor platforms at clinical and commercial scales. You will contribute hands-on to experimental design, process characterization, and scale-up/tech transfer activities from research through IND enabling, partnering closely with Research, Analytical Development, CMC, Regulatory, Manufacturing, Quality, and external CDMOs.

Key Responsibilities:

• Plan and perform experiments to develop and optimize LVV upstream processes for suspension cell culture (transient or stable producer cell systems), targeting improvements in titer, quality, robustness, and cost.

• Execute unit operations across seed, production, and harvest interfaces; support scale-up strategies from bench to pilot and clinical scales; develop and use scale-down models for characterization and comparability.

• Design DOE studies, identify CPPs/CMAs, analyze data, and propose control strategies; document results in protocols and reports; maintain fit for-purpose knowledge records.

• Contribute to definition of design space, in-process controls, and operating ranges; trend process performance and drive troubleshooting, root cause analysis, and corrective actions.

• Prepare technical transfer packages and support transfers to internal GMP sites and CDMOs; align process documentation with cGMP principles for late-stage readiness.

• Work closely with Analytical Development on assay readiness and in process testing; partner with Manufacturing, Supply, and Quality to ensure operational feasibility and compliance.

• Apply Lean practices and digital tools for scheduling, data integrity, and reproducibility; track KPIs (titer, infectivity, impurity profiles, cycle time, right first time) and recommend improvements.

Qualifications:

• Education: Ph.D. in Chemical Engineering, Biochemical Engineering, Biotechnology, or related field with 1+ years of industry experience; OR M.S. with 4+ years; OR B.S. with 5+ years of hands-on industry experience.

• Experience: Hand-on experience developing suspension-based LVV upstream processes; familiarity with clinical/commercial scale considerations, process characterization, and technology transfer.

• Technical Skills: Proficiency in suspension cell culture, transfection/infection strategies, media/feed optimization, single-use rocking-platform and stirred-tank bioreactors, and upstream-harvest interfaces; working knowledge of statistical DOE and data analytics tools.

• GMP Readiness: Experience supporting cGMP interfaces (documentation, change control, sampling plans) and contributing to CMC sections or technical responses is a plus.

• Communication & Teamwork: Strong written and verbal communication skills; ability to work effectively in cross-functional, matrixed teams; demonstrated problemsolving and troubleshooting capability.

• Tools & Automation: Experience with single-use systems, process automation/PAT, and digital lab systems (ELN/LIMS) preferred.

Preferred Qualifications:

• Demonstrated success scaling suspension LVV processes to pilot/clinical scales and sustaining performance via monitoring and continuous improvement.

• Experience linking upstream parameters to analytical outcomes (titer, infectivity/potency, residuals/impurities) to guide process decisions.

• Contributions to regulatory filings (data tables, process descriptions) and participation in tech transfer to CDMOs or internal GMP sites.

• Experience implementing Lean/continuous improvement and robust documentation/knowledge management in PD labs.

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

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

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

Responsibilities

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

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

• Create and maintain comprehensive honesty benchmarks and evaluation frameworks

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

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

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

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

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

Requirements

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

• Possess strong programming skills in Python

• Have industry experience with language model finetuning and classifier training

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

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

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

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

Preferred qualifications

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

• Experience with fact-grounding techniques

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

• A track record of creating and maintaining factual knowledge bases

• Familiarity with RLHF specifically applied to improving model truthfulness

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

• Experience developing evaluations of model accuracy or hallucinations

Benefits

• Competitive compensation and benefits

• Optional equity donation matching

• Generous vacation and parental leave

• Flexible working hours

• Lovely office space in which to collaborate with colleagues

Visa sponsorship

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

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Training on natural and experimentally-derived data is a core aspect of how our AI models learn to generate therapeutic molecules with exceptional properties. We invest deeply in building and scaling data sources to train and evaluate our models for maximal performance. At the same time, careful validation in orthogonal, translationally-relevant assays is crucial to orient our models.

We are seeking a senior scientific leader versed in high-throughput and translational biology to drive the continued growth and impact of our Palo Alto Lab. You will be a force multiplier for our scientists and engineers, ensuring a high standard of scientific rigor and output in a fast-paced, dynamic environment. You will also interface closely with our AI team to maximize the impact of internal data on Inceptive’s foundation models.

Your Mission, should you choose to accept it - Lead development and scale-up of high-throughput assays across in vitro, cellular, and in vivo systems, leveraging multiplexed assays and laboratory automation - Define and execute a lab strategy aligned with Inceptive’s therapeutic and platform priorities, while remaining flexible as modality and partnership needs evolve - Champion an interdisciplinary culture, encouraging curiosity, rigor, and collaboration across scientific boundaries - Manage, mentor, and develop a multidisciplinary team of scientists and engineers that rapidly generates high-impact biological data to improve and validate AI design models - Oversee the development of industry-standard validation assays to keep models and data generation aligned with downstream therapeutic application

Qualifications - PhD and 6+ years of post-PhD experience in industrial research applied to drug development - Experience managing and mentoring a data-driven lab of 10+ scientists - Experience using high-throughput and/or highly multiplexed assays to generate rich datasets from mammalian cells - Proven ability to set scientific direction while also executing operationally - Deep understanding of theory, techniques, and experimental design in molecular and cellular biology - Visualization, analysis, and statistics applied to complex biological datasets - Availability to work with team members across US and Europe, with meetings starting at 7am PT - Readiness to travel several times a year for company retreats and business events - We value in-person collaboration and expect candidates to work at our lab location

Preferred skills - Translational experience with mRNA, oligonucleotides, or other genetic medicines - Expertise in immunology and/or cell therapy - Hands-on experience in RNA biology and biochemistry - Scientific programming in Python - Hands-on experience with modern data engineering workflows

Compensation $245K – $305K + Bonus + Equity

What we offer - A competitive compensation package - 30 days paid vacation per year - Comprehensive health insurance for US based Beginners - 401K with company match for US based Beginners and Direktversicherung for German Beginners - Quarterly company-wide retreats - Monthly wellness benefit - Budget for multiple visits per year to our offices in Berlin, Palo Alto or Switzerland - Learning & Development budget to attend conferences, take courses, or otherwise invest in your professional growth, as well as access to the Learning & Development platform EdX and Hone - A buddy to help you get settled *Varies by country and does not apply to internships

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This is not a reporting role. This role owns end-to-end data products - from problem framing and modeling to deployment and operational integration - that directly influence how our GTM organization prioritizes leads, manages accounts, allocates resources, and drives revenue.

You’ll work closely with Marketing, Sales, and RevOps leadership to build ML-powered systems that change how decisions are made at scale.

What will I be doing?

• Build Revenue-Impacting ML Systems
• Develop, deploy, optimize predictive models (lead scoring, account prioritization, marketing attribution, revenue estimation)
• Productionize models into operational systems (Salesforce, Marketo, outbound workflows)
• Monitor model performance and iterate for measurable business lift
• Design and implement experimentation frameworks (A/B testing, holdouts, incremental lift measurement)
• Apply advanced techniques when appropriate (e.g., causal inference, uplift modeling, segmentation, LTV modeling)

You don’t just build models - you ensure they change behavior.

Own End-to-End Data Products

• Translate ambiguous business problems into clear, measurable objectives
• Define GTM data products vision, success metrics, and roadmap
• Ensure integration into existing workflows and systems
• Lead stakeholder alignment and change management
• Secure buy-in from system owners before replacing or enhancing existing solutions

You operate as a mini GM for your data products.

Architect Scalable Data Foundations

• Design robust data pipelines and modeling infrastructure in collaboration with Data Engineering / Data Infrastructure
• Ensure data quality, governance, and reproducibility
• Elevate the team’s standards for experimentation, documentation, and knowledge sharing
• Push adoption of new tools and AI capabilities where appropriate

You raise the technical bar for the GTM organization.

What impact might I have?

Within 6-12 months, you might:

• Launch predictive models that materially improve conversion, expansion, or retention
• Reduce inefficiencies in Sales workflows through automation
• Help leadership make investment decisions backed by rigorous data science
• Influence GTM strategy through quantitative insight and modeling

Success is measured in business outcomes - not dashboards built.

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You'll collaborate with our technical team to train models on human interactions, problem-solving, and discussions; refine annotation tools; and select/create challenging problems in statistics to boost performance.

All of our AI Tutor roles potentially involve gathering or providing data in text, voice, and video formats, including annotations, audio recordings, or video sessions,tasks with which candidates must be comfortable.

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 statistical domains that align with your expertise, focusing on areas such as probability theory, inferential statistics, regression modelling, multivariate analysis, stochastic processes, Bayesian methods, experimental design, and data-driven applications where you can confidently provide detailed solutions and evaluate model responses.

Basic Qualifications:

• Must have either (a) a Master’s or PhD in Statistics (or Mathematics with a specialisation in statistics or probability) or (b) a medal in an International Math Olympiad (IMO), International Statistical Olympiad, or similar competition.
• Proficiency in reading and writing, both in informal and professional English.
• Strong ability to navigate various information resources and databases.
• Outstanding communication, interpersonal, analytical, and organisational capabilities.
• Solid reading comprehension skills combined with capacity to exercise autonomous judgement even when presented with limited data/material.
• A strong passion for and commitment to technological advancements and innovation.

Preferred Skills and Experience:

• PhD in Statistics or a closely related quantitative field.
• Peer-reviewed publications in statistics, probability, or applied statistical modelling.
• Previous AI Tutoring experience and/or experience teaching college-level statistics courses.

Location and Other Expectations:

• Tutor roles may be offered as full-time, part-time, or contractor positions, depending on role needs and candidate fit.
• For contractor positions, hours will vary widely based on project scope and contractor availability, with no fixed commitments required. On average most projects may involve at least 10 hours per week to achieve deliverables effectively though this is not a fixed commitment and depends on the scope of work. Contractors have full flexibility to set their own hours and determine the exact amount of time needed to complete deliverables.
• Tutor roles may be performed remotely from any location worldwide, subject to legal eligibility, time-zone compatibility, and role specific needs.
• For US based candidates, please note 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 - $75/hour depending on factors including relevant experience, skills, education, geographic location, and qualifications. International candidates: Information will be provided to you during the recruitment process.

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

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As a Data Scientist lead on the GeminiApp team, you are a key partner and co-creator in our product strategy while managing a growing team. You will be instrumental in building a uniquely proactive and powerful assistant by ensuring our strategic decisions are grounded in data.

Key responsibilities include: Partner with PM, engineering, and UX leadership to develop data-driven product strategies across various areas of GeminiApp Translate ambiguous questions into well-defined problems, design experiments, and analyze large complex datasets for insights Develop and implement novel, goal-oriented metrics Build and deploy statistical/ML models to understand our users, enhance product capabilities and personalize user experience Communicate findings & recommendations to stakeholders, including executives Champion data-driven culture by feeding user engagement insights back into models Collaborate with the GenAI team on model quality and feature adoption Act as a technical leader for a global team, guiding junior members on complex analyses and upholding best practices to ensure high-quality, impactful work

We are looking for a bias for action and a relentless drive to build something great. You are a resourceful and creative problem-solver, able to find innovative solutions in a fast-paced and dynamic environment. You are comfortable with ambiguity and thrive on a challenge.

Strong business acumen and a strategic mindset. You have a proven ability to connect data-driven insights to business impact and can effectively translate business needs into data science problems.

Deep technical expertise. You have a strong foundation in statistical modeling, machine learning, and experimental design. You are proficient in SQL and have hands-on experience with a programming language like Python or R.

Exceptional communication and presentation skills. You can articulate complex technical concepts to both technical and non-technical audiences, including executive leadership. You are a compelling storyteller who can use data to influence decisions.

A collaborative and influential partner. You have a track record of successfully collaborating with and influencing cross-functional teams, particularly engineering and product management, to drive data-informed decisions. You are ready to work in an environment with a shared roadmap that holds multiple teams accountable for both model quality and feature adoption.

A commitment to user trust and privacy. You understand the importance of telling users what data is being used and why, and you are committed to providing users with granular, easy-to-understand controls over their personal information.

You must meet the following minimum qualifications to

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Responsibilities:

• Design, develop, and apply DS solutions to inform improvements in advertiser experience and Reddit's ad platform
• Analyze large-scale datasets to identify trends, patterns, and insights that can be used to improve the effectiveness of our advertising platform
• Collaborate with product managers and engineers to define product requirements and translate them into data science solutions
• Develop ML models & DS methods to improve anomaly detection, prediction, & pattern recognition
• Communicate findings and recommendations to stakeholders across the organization
• Stay up-to-date on the latest advancements in machine learning and data science
• Mentor and guide junior data scientists on the team

Qualifications:

• Advanced degree (Masters or Ph.D.) in a quantitative field such as: Statistics, Mathematics, Physics, Economics, or Operations Research
• For M.S. holders: 5+ years of industry experience in applied science or data science roles
• For Ph.D. holders: 4+ years of industry experience in applied science or data science roles
• Platform experience and a deep understanding of the ads ecosystem
• Strong understanding of statistical modeling, machine learning algorithms, causal inference and experimental design
• Experience with large-scale data processing and analysis using tools such as Spark, Hadoop, or Hive; knowledge of BigQuery a plus
• Proficiency in Python or R and experience with machine learning libraries such as scikit-learn, TensorFlow, or PyTorch
• Experience with SQL and relational databases
• Excellent communication and presentation skills

Bonus Points:

• Experience with online advertising and ad tech
• Experience with causal inference and A/B testing
• Contributions to open-source projects or publications in relevant conferences or journals

Benefits:

• Comprehensive Healthcare Benefits and Income Replacement Programs
• 401k with Employer Match
• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave

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

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

Key responsibilities include:

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

Requirements include:

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

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

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

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You'll collaborate with our technical team to train models on human interactions, problem-solving, and discussions; refine annotation tools; and select/create challenging problems in statistics to boost performance.

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 statistical domains that align with your expertise, focusing on areas such as probability theory, inferential statistics, regression modeling, multivariate analysis, stochastic processes, Bayesian methods, experimental design, and data-driven applications where you can confidently provide detailed solutions and evaluate model responses.

Basic Qualifications:

• Must have either (a) a Master’s or PhD in Statistics (or Mathematics with a specialization in statistics or probability) or (b) a medal in an International Math Olympiad (IMO), International Statistical Olympiad, or similar competition.
• Proficiency in reading and writing, both in informal and professional English.
• Strong ability to navigate various information resources and databases.
• Outstanding communication, interpersonal, analytical, and organizational capabilities.
• Solid reading comprehension skills combined with capacity to exercise autonomous judgment even when presented with limited data/material.
• A strong passion for and commitment to technological advancements and innovation.

Preferred Skills and Experience:

• PhD in Statistics or a closely related quantitative field.
• Peer-reviewed publications in statistics, probability, or applied statistical modeling.
• Previous AI Tutoring experience and/or experience teaching college-level statistics courses.

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Responsibilities:

• Analyze large-scale datasets to identify trends, patterns, and insights that can be used to improve the effectiveness of our advertising platform
• Develop ML models & DS methods to for improved anomaly detection, prediction, pattern recognition
• Communicate findings and recommendations to stakeholders across the organization
• Collaborate with product, engineering, sales, and marketing partners to define product and program requirements and translate them into data science solutions
• Stay up-to-date on the latest advancements in machine learning and data science

Qualifications:

• Advanced degree (Masters or Ph.D.) in a quantitative field such as: Statistics, Mathematics, Physics, Economics, or Operations Research
• For M.S. holders: 3+ years of industry experience in applied science or data science roles
• For Ph.D. holders: 2+ years of industry experience in applied science or data science roles
• Strong understanding of statistical modeling, machine learning algorithms, causal inference and experimental design
• Experience with large-scale data processing and analysis using tools such as Spark, Hadoop, or Hive; knowledge of BigQuery a plus
• Proficiency in Python or R and experience with machine learning libraries such as scikit-learn, TensorFlow, or PyTorch
• Experience with SQL and relational databases
• Excellent communication and presentation skills

Bonus Points:

• Experience with online advertising and ad tech
• Experience with causal inference and A/B testing
• Contributions to open-source projects or publications in relevant conferences or journals

Benefits:

• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Comprehensive Medical Benefits & Health Care Spending Account
• Registered Retirement Savings Plan with matching contributions
• Income Replacement Programs
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave

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This role requires a passion for understanding and modeling the interactions between AI and society, a strong awareness of the AI alignment and safety landscape, and a penchant for developing novel ideas, methods, interfaces, and tools.

As a Research Scientist at Google DeepMind, you will join a team working to supercharge exploration, assessment, and steering of evolving AI behaviours, with a focus on subjective and creative tasks. You will tackle the underlying research questions to improve collaborative specification of alignment objectives and assessment of adherence to desired behaviours.

Key responsibilities include generating new ideas, executing cutting-edge ideas, communicating research findings, collaborating with other researchers, and driving technical projects.

To be successful in this role, you will need a PhD degree in Computer Science, Machine Learning, or a related technical field, a strong publication record in top machine learning conferences, and demonstrated hands-on experience in developing multimodal AI models and systems.

In addition, experience with large-scale vision language models, fine-tuning and post-training LLMs using RL, and developing agentic AI solutions to complex problems would be an advantage.

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You'll serve as the central coordinator between Data Science, Growth Marketing, Brand Marketing, Product, Engineering, Data Infrastructure, Privacy, Finance, and external partners including MMM vendors, media platform partners, and agencies. This role requires someone who can navigate technical complexity, drive alignment across diverse stakeholders, and translate between business strategy and technical execution across both performance and brand measurement.

As the program lead for our measurement infrastructure, you'll be responsible for delivering our MMM proof-of-concept, establishing ongoing experimentation frameworks, designing and executing brand lift studies, leading the strategic assessment and migration of infrastructure, and building the operational foundations that enable data-driven marketing investment decisions at scale.

Responsibilities:

• Marketing Measurement Intelligence: Lead end-to-end program management for MMM proof-of-concept execution, and transition to production operations. Design and execute comprehensive incrementality testing programs including geo-based experiments, conversion lift studies, and in-platform tests with media partners to calibrate and validate MMM outputs. Lead brand lift study design and execution across media platforms to measure awareness, consideration, favorability, and intent. Synthesize measurement results across MMM, brand lift, and incrementality testing for holistic marketing effectiveness views, building reporting frameworks that connect brand health metrics to business outcomes.
• MarTech Infrastructure & Vendor Management: Support strategic assessments of marketing technology platforms, facilitating cross-functional evaluation and driving stakeholder alignment on build-vs-buy decisions while mapping dependencies and identifying blockers. Serve as key contact for vendors and agencies, managing relationships, business reviews, and coordinating execution with implementation roadmaps. Establish operational excellence standards including monitoring, alerting, version control, automated privacy validation, and incident response protocols while maintaining executive visibility into platform initiatives and working with Legal and Security on vendor reviews.
• Marketing Workflow Automation: Partner with Marketing leadership to identify, prioritize, and support deployment of AI-powered automation solutions for marketing operations. Establish governance frameworks, quality standards, validation processes, and monitoring mechanisms for automated marketing workflows. Build sustainable operating models for ongoing automation maintenance and continuous improvement. Track and measure automation impact to demonstrate ROI to leadership and cross-functional teams. Act as a center of excellence to socialize successful automation stories within Marketing to the broader Anthropic organisation.

You May Be a Good Fit If You:

• Have 7+ years of technical program management experience, with 3+ years in marketing measurement, analytics infrastructure, or data science programs
• Have a track record of successfully managing complex programs involving data science, marketing operations, engineering, agencies, and vendors
• Possess deep understanding of MMM, attribution, incrementality testing, brand lift studies, and experimentation design
• Have strong technical fluency with customer data platforms, marketing data sources, data warehouses, and analytics platforms
• Have experience evaluating and migrating between marketing technology platforms or data infrastructure systems
• Can engage with data scientists on regression analysis, causality, adstock modeling, and experimental design
• Understand CDP architecture including event collection, tag management, streaming delivery, reverse ETL, and privacy compliance
• Have a track record of delivering 0-to-1 programs on aggressive timelines with high visibility
• Excel at translating technical concepts for varied audiences and can influence without authority
• Thrive in ambiguous situations, bringing structure to complex challenges with competing priorities and limited resources
• Have excellent written and verbal communication skills with executive presence and strong presentation abilities
• Are passionate about Anthropic's mission and interested in the challenges of bringing frontier AI capabilities to market

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As a Research Scientist/Engineer focused on honesty within the Finetuning Alignment team, you'll spearhead the development of techniques to minimise hallucinations and enhance truthfulness in language models. Your work will focus on creating robust systems that are accurate and reflect their true levels of confidence across all domains, and that work to avoid being deceptive or misleading.

Responsibilities:

• Design and implement novel data curation pipelines to identify, verify, and filter training data for accuracy given the model’s knowledge
• Develop specialised classifiers to detect potential hallucinations or miscalibrated claims made by the model
• Create and maintain comprehensive honesty benchmarks and evaluation frameworks
• Implement techniques to ground model outputs in verified information, such as search and retrieval-augmented generation (RAG) systems
• Design and deploy human feedback collection specifically for identifying and correcting miscalibrated responses
• Design and implement prompting pipelines to generate data that improves model accuracy and honesty
• Develop and test novel RL environments that reward truthful outputs and penalize fabricated claims
• Create tools to help human evaluators efficiently assess model outputs for accuracy

You may be a good fit if you:

• Have an MS/PhD in Computer Science, ML, or related field
• Possess strong programming skills in Python
• Have industry experience with language model finetuning and classifier training
• Show proficiency in experimental design and statistical analysis for measuring improvements in calibration and accuracy
• Care about AI safety and the accuracy and honesty of both current and future AI systems
• Have experience in data science or the creation and curation of datasets for finetuning LLMs
• An understanding of various metrics of uncertainty, calibration, and truthfulness in model outputs

Strong candidates may also have:

• Published work on hallucination prevention, factual grounding, or knowledge integration in language models
• Experience with fact-grounding techniques
• Background in developing confidence estimation or calibration methods for ML models
• A track record of creating and maintaining factual knowledge bases
• Familiarity with RLHF specifically applied to improving model truthfulness
• Worked with crowd-sourcing platforms and human feedback collection systems
• Experience developing evaluations of model accuracy or hallucinations

Join us in our mission to ensure advanced AI systems behave reliably and ethically while staying aligned with human values.

The annual compensation range for this role is listed below.

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

Annual Salary:

$350,000 - $500,000USD

Logistics

Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience.

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

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

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

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

How we're different

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single team to push the boundaries of what is possible with AI.

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Anthropic's mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

About the Role:

Anthropic's ML Performance and Scaling team trains our production pretrained models, work that directly shapes the company's future and our mission to build safe, beneficial AI systems. As a Research Engineer on this team, you'll ensure our frontier models train reliably, efficiently, and at scale. This is demanding, high-impact work that requires both deep technical expertise and a genuine passion for the craft of large-scale ML systems.

This role lives at the boundary between research and engineering. You'll work across our entire production training stack: performance optimization, hardware debugging, experimental design, and launch coordination. During launches, the team works in tight lockstep, responding to production issues that can't wait for tomorrow.

Responsibilities:

• Own critical aspects of our production pretraining pipeline, including model operations, performance optimization, observability, and reliability
• Debug and resolve complex issues across the full stack—from hardware errors and networking to training dynamics and evaluation infrastructure
• Design and run experiments to improve training efficiency, reduce step time, increase uptime, and enhance model performance
• Respond to on-call incidents during model launches, diagnosing problems quickly and coordinating solutions across teams
• Build and maintain production logging, monitoring dashboards, and evaluation infrastructure
• Add new capabilities to the training codebase, such as long context support or novel architectures
• Collaborate closely with teammates across SF and London, as well as with Tokens, Architectures, and Systems teams
• Contribute to the team's institutional knowledge by documenting systems, debugging approaches, and lessons learned

You May Be a Good Fit If You:

• Have hands-on experience training large language models, or deep expertise with JAX, TPU, PyTorch, or large-scale distributed systems
• Genuinely enjoy both research and engineering work—you'd describe your ideal split as roughly 50/50 rather than heavily weighted toward one or the other
• Are excited about being on-call for production systems, working long days during launches, and solving hard problems under pressure
• Thrive when working on whatever is most impactful, even if that changes day-to-day based on what the production model needs
• Excel at debugging complex, ambiguous problems across multiple layers of the stack
• Communicate clearly and collaborate effectively, especially when coordinating across time zones or during high-stress incidents
• Are passionate about the work itself and want to refine your craft as a research engineer
• Care about the societal impacts of AI and responsible scaling

Strong Candidates May Also Have:

• Previous experience training LLM’s or working extensively with JAX/TPU, PyTorch, or other ML frameworks at scale
• Contributed to open-source LLM frameworks (e.g., open\_lm, llm-foundry, mesh-transformer-jax)
• Published research on model training, scaling laws, or ML systems
• Experience with production ML systems, observability tools, or evaluation infrastructure
• Background as a systems engineer, quant, or in other roles requiring both technical depth and operational excellence

What Makes This Role Unique:

This is not a typical research engineering role. The work is highly operational—you'll be deeply involved in keeping our production models training smoothly, which means being responsive to incidents, flexible about priorities, and comfortable with uncertainty. During launches, the team often works extended hours and may need to respond to issues on evenings and weekends.

However, this operational intensity comes with extraordinary learning opportunities. You'll gain hands-on experience with some of the largest, most sophisticated training runs in the industry. You'll work alongside world-class researchers and engineers, and the institutional knowledge you build will compound in ways that can't be easily transferred. For people who thrive on this type of work, it's uniquely rewarding.

We're building a close-knit team of people who genuinely care about doing excellent work together. If you're someone who wants to be part of training the models that will define the future of AI—and you're excited about the full reality of what that entails—we'd love to hear from you.

Logistics

Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience. Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

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

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Research Engineer, AI for Science

Location

San Francisco

Employment Type

Full time

Department

Research

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

OpenAI for Science is building the next great scientific instrument: an AI-powered platform that accelerates scientific discovery. We aim to prove that OpenAI’s frontier models can do real science—and help researchers everywhere do more, faster.

About the Role

As a Research Engineer, you will build AI systems that enable previously impossible capabilities or achieve unprecedented levels of performance. You’ll work at the intersection of engineering and research, designing, implementing, and improving large-scale machine learning systems while contributing to the science behind the algorithms themselves.

We’re looking for people with strong engineering fundamentals who enjoy writing high-quality ML code, are comfortable working at massive scale, and are excited about OpenAI’s approach to research. As deep learning systems continue to scale, engineering excellence will play a critical role in driving the next major advances in AI.

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 will:

• Design, implement, and improve large-scale distributed machine learning systems

• Write robust, high-quality machine learning code and contribute to performance-critical components

• Collaborate closely with researchers to translate ideas into scalable, production-ready systems

You might thrive in this role if you:

• Have strong programming skills and enjoy building reliable, high-quality systems

• Are comfortable working in large distributed systems and at significant computational scale

• Are excited about OpenAI’s research direction and motivated by the real-world impact of AI

• Nice to have:

• Interest in using AI to accelerate scientific discovery, improve experimental design, or enable new forms of scientific insight

• Experience building high-performance implementations of deep learning algorithms

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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Location

San Francisco

Employment Type

Full time

Location Type

Hybrid

Department

Data Science

Compensation

• $266K – $385K • 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 UX Research team is a small team with outsized impact across OpenAI. We sit at the intersection of users, product, and safety—helping ensure that powerful AI systems are built responsibly and grounded in real human needs.

Our work informs critical product decisions across OpenAI. We partner closely with product, design, engineering, and leadership to bring clarity to complex questions—often in fast-moving spaces where norms and best practices are still being defined.

This role is based in San Francisco, CA. We operate on a hybrid model with 3 days in the office each week and offer relocation assistance.

In this role, you will:

• Design and execute quantitative research across the product lifecycle, from foundational understanding to concept validation, prototyping, and usability evaluation.

• Partner with product managers, designers, engineers, and data scientists to identify high-impact opportunities where quantitative insights can meaningfully shape product decisions.

• Lead rigorous, customized studies that answer both strategic and tactical questions, using methods such as surveys, experiments, and behavioral data analysis.

• Translate complex data into clear, actionable recommendations that drive alignment and decision-making across teams.

• Apply strong survey methodology and statistical rigor to ensure findings are valid, reliable, and decision-ready.

• Influence product direction through close cross-functional collaboration and clear, audience-appropriate storytelling.

You might thrive in this role if you have:

• 5+ years of experience working in user experience research, market research, data science, and/or a related field with a strong focus on quantitative methods.

• Expertise in quantitative research, with proficiency in statistical analysis, experimental design, survey methodology, and behavioral data analysis.

• Strong data analysis skills using tools such as SQL and Python.

• Exceptional written and verbal communication skills, with the ability to influence decision-making at all levels.

• Proven experience leading quantitative research projects that have made a lasting impact on product and design decisions.

• Experience working with senior stakeholders.

• A drive for excellence and the ability to consistently raise the bar.

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

• Partner with design and product management leaders to break down ambiguous problems, identify key business opportunities, and leverage data to establish essential metrics and deliver insights that will drive and shape the strategic direction.
• Transform raw data into data models, production metrics, scaled reporting, and insights to improve user experience and engagement.

What you need

• 7+ years of industry or relevant experience, with a good understanding of live service video games
• Strong product intuition and ability to shape strategy for a complex ecosystem
• Demonstrated background in influencing products by applying data and measurement to drive alignment

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What you'll do

As a Data Scientist in our team, you will focus on building end-to-end data science solutions from exploratory analysis to model development and performance evaluation working closely with Machine Learning Engineers and Data Engineers.

• Analyze large, multilingual datasets to generate actionable insights for localization workflows.
• Develop and refine feature engineering pipelines tailored for multilingual and multimodal datasets.

What you need

• 2+ years of hands-on experience in applied data science, ideally in NLP, prompt engineering or multilingual domains.

XML job scraping automation by YubHub

What you'll do

• Partner with design and product management leaders to break down ambiguous problems, identify key business opportunities, and leverage data to establish essential metrics and deliver insights that will drive and shape the strategic direction.
• Transform raw data into data models, production metrics, scaled reporting, and insights to improve user experience and engagement.

What you need

• 7+ years of industry or relevant experience, with a good understanding of live service video games
• Strong product intuition and ability to shape strategy for a complex ecosystem

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What you'll do

• Lead the analytical strategy for important game features and player experience projects, aligning insights with product vision and team goals.
• Design and implement advanced frameworks to evaluate player behaviour, feedback systems, and quality metrics across multiple titles.

What you need

• 8+ years in data analytics, with proven experience in gaming, tech, or consumer insights.

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