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🚀 ABOUT WRITER WRITER is where the world's leading enterprises orchestrate AI-powered work. Our vision is to expand human capacity through superintelligence. And we're proving it's possible – through powerful, trustworthy AI that unites IT and business teams together to unlock enterprise-wide transformation. With WRITER's end-to-end platform, hundreds of companies like Mars, Marriott, Uber, and Vanguard are building and deploying AI agents that are grounded in their company's data and fueled by WRITER's enterprise-grade LLMs. Valued at $1.9B and backed by industry-leading investors including Premji Invest, Radical Ventures, and ICONIQ Growth, WRITER is rapidly cementing its position as the leader in enterprise generative AI. Founded in 2020 with office hubs in San Francisco, New York City, Austin, Chicago, and London, our team thinks big and moves fast, and we're looking for smart, hardworking builders and scalers to join us on our journey to create a better future of work with AI. 📐 ABOUT THE ROLE AI research at WRITER isn't just about publishing papers — it's about building the scientific foundation that powers some of the most ambitious enterprise AI deployments in the world. As an AI research scientist, you'll be at the center of that work. You'll drive a high-impact research agenda focused on large language models, agentic reasoning, and the system-level capabilities that make AI genuinely useful at enterprise scale. This is a rare opportunity to do research that matters twice over — advancing the field and shipping directly into products used by hundreds of thousands of people every day. We're at an inflection point. Enterprises are moving from experimenting with AI to deeply embedding it across their operations, and WRITER's models are the engine making that possible. The work you do here — on post-training, planning, multi-step reasoning, and agentic workflows — will directly shape how the next generation of enterprise AI behaves, performs, and scales. You'll have the resources, infrastructure, and cross-functional support to pursue ambitious ideas and bring them to life quickly. This role is hybrid, based out of our San Francisco or New York City hub. You'll report to our VP of AI research. Please note: role is open to Senior, Staff, and Sr. Staff applicants We are open to hiring for this role at multiple levels, with compensation ranges scaled to match your experience, expertise, and the scope of the role. 🦸🏻‍♀️ WHAT YOU'LL DO - Lead an independent, high-impact research agenda on large language models and agentic systems, owning projects from early hypothesis through model training, evaluation, and production deployment - Design and execute large-scale post-training experiments using supervised fine-tuning, reinforcement learning from human feedback (RLHF), RLAIF, DPO, and emerging alignment techniques — with a focus on improving multi-step reasoning, planning, and tool use in enterprise agentic workflows - Build novel evaluation benchmarks and methodologies that push beyond existing limitations, establishing rigorous measures for how well models perform on complex, real-world enterprise tasks - Develop scalable data synthesis and curation pipelines that generate the high-quality training signal driving model improvement — including LLM-as-judge frameworks, synthetic data generation, and adversarial dataset construction - Shape WRITER's model architecture and training roadmap by translating your research insights into concrete improvements to our enterprise-grade LLMs, working hand-in-hand with research engineering and product teams - Publish and present original research at top-tier venues — NeurIPS, ICLR, ICML, ACL, and others — representing WRITER at the frontier of the field and contributing to the broader scientific community - Mentor and uplevel fellow researchers and engineers on the team, helping set a high bar for scientific rigor, experimental design, and research culture ⭐️ WHAT YOU NEED - 7+ years of hands-on ML research experience, with deep expertise in large language model pre-training and post-training — you've trained models at scale, debugged distributed jobs, and shipped improvements that made a measurable difference - A Ph.D. in Computer Science, Machine Learning, NLP, or a related field — or equivalent demonstrated research experience with a strong portfolio of independent, published work - Expert-level knowledge of post-training methods including SFT, RLHF, RLAIF, DPO, GRPO, and related alignment and reasoning techniques, with a track record of applying them to real, production-grade systems - Strong command of Python and PyTorch (or JAX), with the engineering depth to build and scale training pipelines, evaluation infrastructure, and data synthesis workflows yourself — not just direct others to do it - A meaningful publication record at competitive ML/AI venues (NeurIPS, ICLR, ICML, ACL, EMNLP, or equivalent), evidencing your ability to originate ideas and execute on a multi-month research agenda independently - Hands-on experience designing or evaluating agentic systems — models that plan, reason through multi-step tasks, use tools, and recover gracefully from errors — with a nuanced understanding of where they break and how to fix them - The instincts and orientation that match WRITER's values: you Connect — you collaborate openly across research, engineering, and product and communicate complex ideas with clarity to both technical and non-technical audiences; you Challenge — you ask the hard questions, push back on conventional wisdom, and pursue the research directions others haven't tried yet; you Own — you drive your projects end-to-end with urgency, take accountability for results, and care deeply about the impact your work has on real customers 🍩 Benefits & perks (US Full-time employees) - Generous PTO, plus company holidays - Medical, dental, and vision coverage for you and your family - Paid parental leave for all parents (16 weeks) - Fertility and family planning support - Early-detection cancer testing through Galleri https://www.galleri.com/partner/writer - Flexible spending account and dependent FSA options - Health savings account for eligible plans with company contribution - Annual work-life stipends for: - Wellness stipend for gym, massage/chiropractor, personal training, etc. - Learning and development stipend - Company-wide off-sites and team off-sites - Competitive compensation, company stock options and 401k WRITER is an equal-opportunity employer and is committed to diversity. We don't make hiring or employment decisions based on race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other basis protected by applicable local, state or federal law. Under the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. By submitting your application on the application page, you acknowledge and agree to WRITER's Global Candidate Privacy Notice https://writer.com/legal/candidate-privacy-notice/.

Listed by Writer for a position based in the United States. Employers on this board attest they are hiring domestically.

Science

43 days ago

Principal, User Research

MURAL · United States

Pay

$172k–245k

Setting

Remote

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ABOUT THE TEAM At Mural, we believe great collaboration starts with deep understanding. Our mission is to help teams think and work together better. The Design and Research team uncovers the truths that power that mission, guiding product, design, and strategy through rigorous, human-centered inquiry. We combine behavioral science, market insight, and creative exploration to shape Mural’s future for how teams ideate, align, and collaborate together across the world. YOUR MISSION As the Principal, User Researcher at Mural, you’ll start a UX research practice and lead foundational and strategic research that shapes how the company defines its next generation of experiences. You’ll partner across product, design, sales, marketing, and strategy to identify new opportunity spaces, clarify evolving user needs, and guide the organization toward long-term innovation. This is a primarily individual-contributor role focused on uncovering deep human collaboration insights that drive strategy, innovation, and long-term vision. You’ll also help shape and scale the UXR discipline at Mural by mentoring designers to confidently run tactical usability studies, and establishing the frameworks and best practices that elevate research across the company. Think of it as being the first research leader at a fast-growing startup, with the reach and resources of a global platform. WHAT YOU'LL DO Player Responsibilities (Individual Contributor Work): - Lead mixed-methods research (qualitative and quantitative) that explores user needs, behaviors, and motivations across multiple product areas. - Drive foundational studies that reveal how teams collaborate and what barriers exist in business collaboration, hybrid, and distributed work. - Design and execute medium to large-scale studies that combine qualitative depth with quantitative rigor (surveys, logs analysis, segmentation, and concept testing). - Develop a tempo where actionable insights are timely and urgently positioned to shape key product decisions. - Translate ambiguous questions into clear learning plans and frameworks that guide product and strategy decisions. - Build artifacts (archetypes, frameworks, journey maps, mental models) that make complex insights accessible and actionable across the company, leveraging Mural products. - Present insights to an executive, cross-functional audience and provide strategic recommendations based on these insights. Coach Responsibilities: - Build the research practice: mentor designers, and product partners in research best practices, helping to scale a culture of curiosity and evidence-based decision making. - Establish repeatable, high-quality research standards and methodologies across teams. - Partner with design and product leadership to shape Mural’s long-term research vision and roadmap. - Champion the role of research in early product strategy and company-wide initiatives. Hybrid Responsibilities (Both Player & Coach): - Collaborate closely with cross-functional leaders to prioritize research that informs Mural’s most critical next-generation bets. - Facilitate workshops and storytelling sessions that bring insights to life and influence direction across product, design, and business strategy. - Partner with Data Science and Market Research to integrate behavioral data, attitudinal insights, and business signals into cohesive, actionable narratives. - Shape how research connects to strategy, innovation, and experimentation at every level of the company. WHAT YOU'LL BRING - 10+ years of UX Research experience, including deep expertise in both qualitative and quantitative methods. PhD optional. - Proven track record leading foundational and strategic research that influenced product direction, vision, or long-term investments. - Ability to design and execute mixed-methods research independently: from ethnographic and in-depth interviews to survey design and statistical analysis. - Scale strategic insights: Experience driving organizational understanding through storytelling, synthesis, and actionable frameworks. - Strong systems thinking skills, with an ability to connect human insight to product architecture and long-term design strategy. - Experience shaping and scaling research practices in growing organizations. - Comfortable working in ambiguity and helping cross-functional teams find clarity and alignment. - Strong communicator who can engage both executive and hands-on audiences with empathy, clarity, and conviction. WHY YOU'LL LOVE MURAL You’ll shape new ways of working, as we interact with AI, team members, and customers. You’ll work on some of the most compelling and open-ended questions about the future of collaboration: how people align, make decisions, and innovate. You’ll have the freedom to define the big questions, run the right studies, and guide the company toward its next horizon. At Mural, we “drink our own champagne” and leverage our product for online collaboration. This role is U.S. Remote. Your work will inform the strategy of a rapidly scaling company that believes research is the compass, not just the map. EQUAL OPPORTUNITY We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

Listed by MURAL for a position based in the United States. Employers on this board attest they are hiring domestically.

Science

44 days ago

Head of Quantitative Research

Range · New York, New York, United States

Pay

$250k–350k

Setting

On-site

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Range is creating AI-powered solutions to eliminate financial complexity for our members. We’re transforming wealth management through the perfect blend of cutting-edge technology and human expertise. We’re obsessed with member experience! We’ve built an integrated platform that tackles the full spectrum of financial needs–investments, taxes, retirement planning, and estate management–all unified in one intuitive system. Backed by Google's Gradient Ventures and Cathay Innovation, we're in hyper-growth mode and looking for exceptional talent to join our starting lineup. Every Ranger at this stage is shaping our culture and way of life—from former CEOs and startup founders to experts from leading hedge funds and tech companies. If you're ready to build something that truly matters in financial services, bring your talent to Range. Here, you'll make a genuine impact on how people manage their financial lives while working alongside a team that celebrates wins, makes big decisions, and blazes new trails together ABOUT THE ROLE As Range's Head of Quantitative Research, you will own the research and modeling behind how every member's portfolio gets built, rebalanced, and managed for taxes, from the models under our portfolio construction to the rules that make tax-loss harvesting and direct indexing work at scale. You will report to our CIO, working closely with Investment Operations and Engineering to move your research into production and with Compliance to keep it within our fiduciary obligations. We're excited to hire this role in Range's New York City office. All of our positions follow an in-office schedule Monday through Friday, allowing you to collaborate directly with your team. If you're not currently based in the area but love what you see, let's discuss relocation as part of your journey to joining us. WHAT YOU’LL DO WITH US - Own the design and ongoing refinement of Range's core portfolio construction methodology, including asset allocation, security selection, and rebalancing logic - Build rigorous backtests to validate model changes, weighing tradeoffs between tracking error, tax efficiency, and transaction costs - Lead research on tax-aware strategies, including tax-loss harvesting and direct indexing, and turn the findings into production rules - Partner with Engineering to turn research into production code, and monitor live portfolio and rebalancing behavior after launch - Evaluate new data sources, market data vendors, and modeling approaches that could improve member outcomes - Present research findings and model changes to the CIO and Investment Committee in plain terms - Share your insights beyond our walls by contributing to published market commentary, and representing Range at conferences and in the media - Work with Compliance and Legal to confirm new strategies hold up under our Advisers Act obligations and Range's fiduciary standard WHAT WILL SET YOU APART - 9+ years of experience in quantitative research, portfolio management, or investment strategy, ideally at a digital wealth management or asset management firm - Bachelor's degree in a highly quantitative field such as statistics, mathematics, economics, or financial engineering; advanced degree or CFA progress a plus - Strong grounding in portfolio theory, including mean-variance optimization, factor models, and risk-adjusted return analysis - Fluency in Python and SQL for research and production work; familiarity with portfolio risk tools like Barra, Axioma, or Aladdin, or data vendors like Bloomberg or FactSet, a plus - Direct experience building or maintaining tax-aware investment strategies, including tax-loss harvesting or direct indexing - Experience with tax-aware long/short extensions and concentrated stock diversification - A track record of shipping research into production, not just publishing findings; FinTech, RIA, or broker-dealer experience a plus - Clear communication skills, with comfort moving between deep research and fast turnaround requests BENEFITS - Health & Wellness: 100% employer-covered medical insurance for employees (75% for dependents), plus dental and vision coverage - 401(k): Retirement savings program to support your future - Paid Time Off: Dedicated time to reset and recharge plus most federal holidays - Parental Leave: Comprehensive leave policy for growing families - Meals: Select meals covered throughout the week - Fitness: Monthly movement stipend - Equity & Career Growth: Early exercise eligibility and a strong focus on professional development - Annual Compensation Reviews: Salary and equity refreshes based on performance - Boomerang Program: After two years at Range, you can take time away to start your own company. We’ll hold your spot for 6 months - and pause your equity vesting, which resumes if you return Range is proud to be an equal opportunity workplace. We are committed to equal employment opportunities regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. As a company, we are committed to designing products, building a culture, and supporting a team that reflects the diverse population we serve.

Listed by Range for a position based in the United States. Employers on this board attest they are hiring domestically.

Science

58 days ago

Senior ML Research Scientist

Rad AI · San Francisco, California, United States

Pay

$170k–220k

Setting

Remote

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ABOUT RAD AI At Rad AI, we’re on a mission to transform healthcare with artificial intelligence. Founded by a radiologist, our AI-driven solutions are revolutionizing radiology—saving time, reducing burnout, and improving patient care. With one of the largest proprietary radiology report datasets in the world, our AI has helped uncover hundreds of new cancer diagnoses and reduced error rates in tens of millions of radiology reports by nearly 50%. Rad AI has secured over $140M in funding, including a recently oversubscribed Series C ($68M round) led by Transformation Capital, bringing our valuation to $528M. Our investors include Khosla Ventures, World Innovation Lab, Gradient Ventures, Cone Health Ventures, and others—all backing our mission to empower physicians with cutting-edge AI. Our latest advancements in generative AI are used by thousands of radiologists daily, supporting more than one-third of radiology groups and healthcare systems and nearly 50% of all medical imaging in the U.S. at partners including Cone Health, Jefferson Einstein Health, Geisinger, Guthrie Healthcare System, and Henry Ford Health. Recognized as one of the most promising healthcare AI companies by CB Insights and AuntMinnie https://www.radai.com/news/auntminnie-recognizes-rad-ai-omni-reporting-as-2023s-best-new-radiology-software, and ranked by Deloitte https://www2.deloitte.com/us/en/pages/technology-media-and-telecommunications/articles/fast500-winners.html as the 19th fastest-growing company in North America, we are building AI-powered solutions that make a real impact. Most recently, Rad AI was named to CNBC’s Disruptor 50 https://www.cnbc.com/2025/06/10/2025-cnbc-disruptor-50-see-the-full-list-of-companies.html list, highlighting the innovation and momentum behind our mission. If you’re ready to shape the future of healthcare, we’d love to have you on our team! WHAT YOU’LL DO - Own a multimodal ML work-stream from problem definition through experimentation, evaluation, deployment, and iteration. - Translate clinical and product needs into clear ML objectives, data strategies, model approaches, and success criteria. - Build and evaluate modern ML systems, including transformers, self-supervised learning, weak supervision, detection, localization, and segmentation. - Work with image, report, and other clinical data to develop systems that are useful in real radiology workflows. - Design rigorous evaluations that go beyond aggregate offline metrics, including clinically meaningful operating points, robustness, calibration, and performance across relevant data slices. - Partner with engineering to productionize models, make practical system tradeoffs, and learn from performance after launch. - Investigate failure modes such as laterality errors, poor image or report grounding, hallucination, dataset bias, domain shift, and workflow disruption. - Communicate research findings and technical decisions clearly through design documents, experiment reviews, and presentations to technical and clinical partners. - Contribute to the research roadmap by identifying promising approaches, sharing learnings, and helping the team decide what to pursue next. - Mentor less experienced researchers and engineers through project collaboration, code and experiment reviews, and technical guidance. WHAT WE’RE LOOKING FOR - Strong applied experience in computer vision, NLP, or deep learning, with a track record of independently designing experiments, analyzing results, and turning findings into working systems. - Experience owning substantial ML projects across the full lifecycle, from data and modeling through production delivery. - Deep hands-on ability in Python and PyTorch, with strong intuition for model architecture, data quality, experimentation, and evaluation. - Experience with modern vision or multimodal techniques such as vision transformers, contrastive learning, masked image modeling, or weak supervision, etc. - The judgment to connect model performance to real user and clinical outcomes, including knowing when a benchmark improvement is not enough. - Strong collaboration skills across research, engineering, product, data, and clinical teams. - Clear written and verbal communication, including the ability to explain technical tradeoffs to both ML experts and clinical partners. - Typically 4+ years of relevant applied ML research or engineering experience, or equivalent scope and impact. We calibrate on demonstrated ownership rather than title or exact tenure. - An MS, PhD, or equivalent practical experience in Computer Science, Electrical Engineering, Machine Learning, Biomedical Engineering, or a related quantitative field. NICE TO HAVE - Experience with medical imaging, radiology, healthcare, or another high-stakes application area. - Familiarity with chest X-ray, CT, MRI, mammography, or other clinical imaging modalities. - Experience with DICOM, image-report pairing, medical data de-identification, radiology workflows, or clinically derived labels. - Experience evaluating models across patients, sites, scanner vendors, protocols, or other sources of distribution shift. - Familiarity with clinical validation, FDA or HIPAA considerations, or other regulated and privacy-sensitive environments. - Experience with 3D vision, longitudinal imaging, report generation, or clinical decision support. - Publications, open-source contributions, or other evidence of research credibility. WHAT SUCCESS LOOKS LIKE You’ll own and advance a meaningful research track from ideation through production. You’ll establish a strong understanding of the clinical problem, build a credible data and evaluation strategy, deliver models that perform reliably in practice, and help the team learn from real-world use. You’ll also become a trusted technical partner to the researchers, engineers, product leaders, data teams, and clinicians working on the broader ML roadmap. Over time, you’ll help raise the quality of research and technical decision-making through strong experimentation, clear communication, and thoughtful mentorship. OUR WORKING STYLE We’re a remote-first company with a highly collaborative, mission-driven research and engineering culture. We value direct communication, intellectual honesty, strong ownership, and practical judgment. The best work here comes from people who can go deep technically, stay close to the clinical context, and make progress even when the problem and the path are not fully defined. This role is U.S. remote, with San Francisco Bay Area preferred. We encourage people from a wide range of backgrounds to apply. If the scope of this role excites you but your experience does not match every bullet, we would still love to hear from you. Join our world-class team as we build and deploy AI solutions that empower physicians and transform patient care—making a meaningful impact on millions of lives. Driven by our mission, we prioritize transparency, inclusion, and close collaboration, bringing together exceptional people to revolutionize healthcare. If you're passionate about driving innovation and delivering impactful healthcare solutions, we'd love to hear from you! To learn more about what it's like to work at Rad AI, visit https://www.radai.com/life-at-rad-ai and be sure to follow us on LinkedIn https://www.linkedin.com/company/radai/?utm_campaign=Recruiting_2026&utm_content=recruiting-job-posting-website&utm_source=recru%5B%E2%80%A6%5Db-posting-website to stay up to date! Location Details: For roles listed as San Francisco - Onsite: - This role will be based in our San Francisco office and we expect employees to work onsite four days per week. The remaining time may be worked remotely or onsite, depending on team and business needs. For roles listed as United States - Remote: - This role is open to candidates located anywhere in the United States. For roles listed as San Francisco - Onsite + United States - Remote: - We will prioritize candidates who can work onsite four days per week in San Francisco, while also considering remote candidates located anywhere in the United States. For US-Based Full-Time Roles, Rad AI offers a variety of benefits, including: - Comprehensive Medical, Dental, Vision & Life insurance - HSA (with employer match), FSA, & DCFSA - 401(k) - 11 Paid Company Holidays - Flexible PTO policy - Annual company-wide offsite - Periodic team offsites - Annual equipment stipend - For roles based outside the US, your recruiter can share more details At Rad AI, we value diversity and provide equal employment opportunities (EEO) to all employees and applicants without regard to race, color, religion, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance. Please be vigilant regarding job scams. We advise all candidates to apply directly through our official careers page. Our recruiters will use email addresses with the domain @radai.com http://radai.com or no-reply@ashbyhq.com.

Listed by Rad AI for a position based in the United States. Employers on this board attest they are hiring domestically.

Science

66 days ago

Product Operations Manager, Research Services

Mercor · San Francisco, California, United States

Pay

$140k–210k

Setting

On-site

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ABOUT MERCOR Mercor's mission is to organize human intelligence to power the AI economy. We're a leading AI data company, building the layer between human expertise and frontier models. Millions of domain experts on the platform are paid over $4 million per day to train frontier AI models. Mercor's APEX benchmark family measures AI's real-world impact on professional work. Mercor Enterprise brings this same infrastructure to Fortune 500 companies: helping companies capture how their best people actually work, translating that expertise directly back into agents. Mercor is creating a new category of work where expertise powers AI advancement. Achieving this requires an ambitious, fast-paced and deeply committed team. You’ll work alongside researchers, operators, and AI companies at the forefront of shaping the systems that are redefining society. Mercor is a profitable Series C company valued at $10 billion. We work in-person five days a week in our San Francisco, NYC, or London offices. ABOUT THE ROLE As a Product Operations Manager, Research Services, you'll drive operational excellence to support Mercor's full-service research partnerships. You will prioritize and manage delivery across various strategic customer segments to support model evaluations, diagnose model capability gaps, and fulfill post-training demand to better support our most strategic customers. This is a highly technical, internally-facing role in the Product Operations job family at the intersection of Product, Engineering, Data Production, GTM, Finance, and Strategic Partnerships. WHAT YOU'LL DO - Prioritize the Benchmark Portfolio: Own the intake and prioritization of new benchmarks and evaluations supported in our platform. Weigh customer demand, observed capability gaps, differentiation versus public benchmarks, and build cost to inform our priorities. - Support Dataset Demand Generation: Run and share leaderboard evals to drive Mercor’s research brand equity during new model releases. - Manage Training and Inference Partners & Budgets: Own the relationships with our inference providers, compute partners, and external training vendors. Forecast capacity against the delivery calendar, negotiate and track SLAs and rate cards, monitor cost per eval run and per rollout, and qualify new partners before we need them. - Track Customer Delivery: Maintain the operating picture across every active evals, loss analysis, and post-training engagements, highlighting scope, milestones, dependencies, and SLA status. Run the delivery review, escalate slipping commitments before the customer notices, and give research counterparts a straight answer on where things stand. - Shape the Product: Translate recurring delivery friction into product requirements for the eval platform and partner with Engineering to automate the workflows you'd otherwise be running by hand. WHAT WE'RE LOOKING FOR - Experience: 3+ years in Product Operations, Product Management, Technical Program Management, Research Operations, Solutions Engineering, or a similar technical, customer-facing role. Experience operating in an ML research or AI infrastructure environment strongly preferred. - Technical Fluency: Fluent in how modern LLM evaluation works, including harness design, verification, agentic rollouts, and contamination and fairness pitfalls. Working understanding of post-training (SFT, preference ranking, RL) and of inference economics. Familiar with coding agents; comfortable in SQL and Python without agent assistance. - Vendor and Capacity Judgment: Can plan capacity against an uncertain demand curve, hold partners to an SLA, and weigh cost against reliability without needing to escalate every call. - Ownership: Thrive in ambiguous environments and take ownership from problem definition through execution. Comfortable being the person accountable for a date. - Communication: Can hold your own in a technical conversation with AI researchers and write a status update an executive can act on. Excellent written and verbal communication. - Systems Thinking: Strong project management and cross-functional coordination skills. Passion for fixing problems at the source and building repeatable systems rather than one-off solutions. Benefits - Bi-annual performance bonus structure - Generous equity grant vested over 4 years - Up to $15k Relocation bonus - $10K housing bonus (if you live within 0.5 miles of our office) - $1.5K monthly stipend for meals - Free Equinox membership - $200 monthly laundry reimbursement - $200 monthly personal wellness reimbursement - Health, Dental, Vision insurance

Listed by Mercor for a position based in the United States. Employers on this board attest they are hiring domestically.

Science

67 days ago

Research Engineer – Benchmarking

Mercor · San Francisco, California, United States

Pay

$180k–500k

Setting

On-site

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ABOUT MERCOR Mercor's mission is to organize human intelligence to power the AI economy. We're a leading AI data company, building the layer between human expertise and frontier models. Millions of domain experts on the platform are paid over $4 million per day to train frontier AI models. Mercor's APEX benchmark family measures AI's real-world impact on professional work. Mercor Enterprise brings this same infrastructure to Fortune 500 companies: helping companies capture how their best people actually work, translating that expertise directly back into agents. Mercor is creating a new category of work where expertise powers AI advancement. Achieving this requires an ambitious, fast-paced and deeply committed team. You’ll work alongside researchers, operators, and AI companies at the forefront of shaping the systems that are redefining society. Mercor is a profitable Series C company valued at $10 billion. We work in-person five days a week in our San Francisco, NYC, or London offices. ABOUT THE ROLE As a Research Engineer at Mercor, you’ll work at the intersection of engineering and applied AI research. You’ll own benchmarking pipelines, evaluation systems, and failure analysis workflows that directly inform how we train and improve frontier language models. Your work will define how we measure tool use, agentic behavior, and real-world reasoning. You’ll design and run evals, build rubrics and scorers, and turn failure analysis into actionable improvements for post-training, RLVR, and data pipelines. WHAT YOU’LL DO - Benchmarking: Design, implement, and maintain benchmarks and metrics for tool use, agentic behavior, and real-world reasoning; ensure benchmarks scale with training and stay aligned with product and research goals. - Evaluation systems: Build and operate LLM evaluation systems end-to-end runs, scoring, dashboards, and reporting, so researchers and applied AI teams can track model performance and compare runs at scale. - Failure analysis: Run systematic failure analysis on model outputs (e.g., wrong tool use, reasoning errors, safety/alignment issues); categorize failure modes, quantify prevalence, and feed findings into reward design, data curation, and benchmark design. - Rubrics and evaluators: Create and refine rubrics, automated evaluators, and scoring frameworks that drive training and evaluation decisions; balance rigor with scalability (human vs. model-as-judge, calibration, agreement). - Data quality and usability: Quantify data usability, quality, and impact on key benchmarks; use evals and failure analysis to guide data generation, augmentation, and curation. - Cross-team collaboration: Work with AI researchers, applied AI teams, and data producers to align evals with training objectives and to prioritize benchmarks and failure analyses that matter most. - Ownership in a fast-paced environment: Operate in a high-iteration research setting with strong ownership of benchmarks, evals, and failure-analysis workflows. WHAT WE’RE LOOKING FOR - Strong applied research background, with focus on model evaluation, benchmarking, and/or failure analysis. - Strong coding skills and hands-on experience with ML models and evaluation code. - Solid grasp of data structures, algorithms, and backend systems. - Comfort with APIs, SQL/NoSQL, and cloud platforms for running and storing eval results. - Ability to reason about model behavior, experimental results, and data quality from evals and failure analyses. - Excitement to work in person in San Francisco five days a week in a high-intensity, high-ownership environment. NICE TO HAVE - Industry experience on a post-training or evaluation/benchmarking team (highest priority). - Publications at top-tier venues (NeurIPS, ICML, ACL), especially in evaluation or benchmarking. - Experience building or running LLM evaluations, benchmarks, or failure-analysis pipelines. - Experience with synthetic data generation, rubric design, or RL-style workflows that use evals for reward shaping. - Work samples or code (e.g., eval frameworks, benchmark suites, failure-analysis reports or tooling) that demonstrate relevant skills. BENEFITS - Bi-annual performance bonus structure - Generous equity grant vested over 4 years - Up to $15k Relocation bonus - $10K housing bonus (if you live within 0.5 miles of our office) - $1.5K monthly stipend for meals - Free Equinox membership - $200 monthly laundry reimbursement - $200 monthly personal wellness reimbursement - Health, Dental, Vision insurance

Listed by Mercor for a position based in the United States. Employers on this board attest they are hiring domestically.

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