Tech Lead, Applied AI - Evals

Mercor

Job details

  • ONSITE
  • FULL_TIME
  • San Francisco
  • United States
  • Verified 2026-11-10
  • Salary: USD 260,000–500,000/yr
  • Source: Mercor public ASHBY source

Original job description

About Mercor

Mercor’s mission is to organize human intelligence for the AI economy. We build the infrastructure that enables frontier AI labs and enterprises to train, evaluate, and improve AI on real-world professional work. More than five million experts have joined our network, and we pay out over $5 million daily for their knowledge and expertise.

We built our training and evaluation infrastructure alongside the world’s leading AI labs. Now, we’re bringing those capabilities to enterprises across industries, enabling them to train, evaluate, and improve AI using their own expertise and standards. Our APEX benchmarks measure how AI performs on economically valuable work, while our enterprise evaluations and post-training capabilities turn those insights into measurable improvements across real-world workflows.

Our work sits at the intersection of frontier AI, human expertise, and real-world application. We’re solving problems few companies have encountered, with the opportunity to influence what the world’s most advanced AI systems become capable of doing. We’re looking for people who bring different perspectives, take ownership, exercise sound judgment, and hold themselves to an exceptionally high standard. You’ll have the opportunity to do consequential work alongside talented colleagues who challenge one another, collaborate openly, and share a commitment to excellence.

Mercor is profitable and recently raised a $750 million Series D at a $20 billion valuation. We work in person five days a week in San Francisco, New York, and London.

About the Role

Mercor’s evals product helps frontier labs and enterprises understand how their models perform on real work. Labs use it to decide what to train next, and enterprises use it to decide which models and agents to trust. It runs evals at scale, grades every result and explains why a model fails. The team also runs APEX, Mercor's family of benchmarks built with domain experts to measure how well frontier models do professional work in fields like law, finance and consulting. Its public leaderboard ranks the latest models, and its results appear in model cards across the industry.

As the Tech Lead on the Evals team, you will own the evals product end to end. You will decide what the team builds next and stay hands-on in the code. The hard problems are in grading open-ended professional work reliably, keeping results reproducible as models and tasks change, and running long agent tasks at scale. The work is becoming as much a research problem as an engineering one.

This role grows with the platform, from evals into post-training and new product areas. You will help turn the failures we find into data that improves models.

What You'll Do

  • Own the evals flywheel and its direction: Set the architecture and roadmap, and make the tradeoff calls in design reviews.

  • Lead the product customers use to evaluate models: Ship the APIs, data models and UI that labs and enterprises use to run evals and compare models.

  • Power APEX launches: Build the systems that run every new frontier model on APEX and publish correct, defensible results to the public leaderboard.

  • Explain why models fail: Build failure analysis that links each failure pattern to the exact steps that went wrong.

  • Set the quality bar for evals: Calibrate graders against expert judgment and decide when a grader or agent change is ready to ship.

  • Keep production healthy: Make sure the product stays reliable and its compute costs stay in check.

  • Work directly with customers: Lead pilots with labs and enterprises and bring what you learn back into the roadmap.

  • Grow the team: Hire and mentor engineers, and manage the people on the team.

What We Are Looking For

  • Bachelor's Degree in Computer Science or a related field

  • 5+ years building and running backend systems in production, with time at senior or staff level

  • Strong full-stack skills in a modern backend language (Python, Go or TypeScript) and a frontend framework such as React

  • A track record of owning a platform or product area end to end, including leading the team that built it

  • Strong product sense that starts from what the user needs

  • Experience building data-heavy products: data models, APIs and views over large volumes of results

  • Excellent written and verbal communication with engineers, researchers and customers

  • Comfort with ambiguity and a habit of shipping iteratively

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

Mercor is an Equal Opportunity Employer and is committed to providing equal opportunity to all employees and applicants. Mercor does not discriminate based on actual or perceived race, color, creed, religion, national origin, ancestry, citizenship status, age, sex or gender (including pregnancy, childbirth, related medical conditions and lactation), gender identity or gender expression, sexual orientation, marital status, military service and veteran status, disability, protected medical condition as defined by California or local law, genetic information, or any other characteristic protected by applicable federal, California, or local laws and ordinances. Further, Mercor prohibits discrimination, harassment, and retaliation based on any combination of protected characteristics. This Policy applies to all areas of employment, including recruitment, hiring, training, promotion, compensation, benefits, discipline, termination, and all other privileges, terms, and conditions of employment. This Policy and the law prohibit employment discrimination against any employee or applicant based on any legally protected status.

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