Bachelor's Degree in Computer Science or related field
Strong full-stack skills in modern backend languages (Python, Go, TypeScript) and frontend frameworks (React)
Proven experience owning product features from concept to production
Strong product sense focused on user needs
Experience building data-heavy products, including data models and APIs
Excellent communication skills with diverse stakeholders
Comfortable with ambiguity and iterative shipping
Experience with LLM evals or AI developer tools is a plus
Startup or B2B developer product experience is a plus
Responsibilities
Build APIs, data models, and UI for model evaluation
Own APEX launches and publish results to the public leaderboard
Develop failure analysis to help customers understand model failures
Create dataset views and registries for benchmark management
Facilitate customer onboarding and self-service capabilities
Engage directly with customers to gather feedback and shape the product roadmap
Benefits
Bi-annual performance bonus structure
Generous equity grant vested over 4 years
Up to $15k relocation bonus
$10K housing bonus for proximity to office
$1.5K monthly stipend for meals
Free Equinox membership
$200 monthly laundry reimbursement
$200 monthly personal wellness reimbursement
Health, Dental, Vision insurance
Full Job Description
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
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)
