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
Mercor’s evals platform 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 a Software Engineer on the Evals product team, you will build the scorecards, failure reports and dataset views that help customers turn eval runs into decisions. You will solve hard problems in scale, grading accuracy and reproducibility, while keeping the product simple to use.
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
Build the product customers use to evaluate models: Ship the APIs, data models and UI that help customers run evals, compare models and share scores.
Own APEX launches: Run every new frontier model on APEX and publish correct, defensible results to the public leaderboard.
Explain why models fail: Build failure analysis that helps customers see where their models fail, with each pattern linked to the exact steps that went wrong.
Make benchmarks easy to find and manage: Build dataset views, registries and versioning that help customers find the right benchmark or bring their own.
Take customers from first login to self-serve: Build onboarding, roles, key management and usage views that help new teams run evals on their own.
Work directly with customers: Join pilots with labs and enterprises and turn what they need into the roadmap.
What We Are Looking For
Bachelor's Degree in Computer Science or a related field
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 product features end to end, from idea to production
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
Experience with LLM evals, benchmarks or AI developer tools is a plus
Startup experience or experience building B2B developer products is a plus
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
Skills Required
- Bachelor’s degree in Computer Science or a related field
- Strong full-stack skills in Python, Go, or TypeScript and a frontend framework such as React
- Track record of owning product features end to end, from idea to production
- Strong product sense focused on user needs
- Experience building data-heavy products with data models, APIs, and views over large result volumes
- Excellent written and verbal communication with engineers, researchers, and customers
- Comfort with ambiguity and iterative shipping
- Experience with LLM evaluations, benchmarks, or AI developer tools
- Startup experience or experience building B2B developer products
Mercor Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Mercor and has not been reviewed or approved by Mercor.
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Fair & Transparent Compensation — Pay is considered competitive across many roles, with clear hourly ranges and an hourly/pay‑per‑task mix designed to align rates with expertise. The structure emphasizes transparent, appropriate pay levels and guarantees payment for legitimate logged time.
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Strong & Reliable Incentives — Payments are processed on a predictable weekly cadence via Stripe/Wise, and some tracks offer additional weekly bonus incentives for top performers. This combination of regular payouts and performance bonuses supports dependable earnings when projects are active.
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Equity Value & Accessibility — Select full‑time roles include generous equity grants alongside cash perks such as relocation and housing bonuses. These elements increase total compensation for those positions.
Mercor Insights
What We Do
We use AI to understand human ability and match talent with the opportunities they're best suited for.








