2 days ago
Base Salary
$220k - $250k/yr
Responsibilities
- Build APIs, data models, and user interfaces for customers to run evaluations, compare models, and share scores.
- Own APEX benchmark launches by running frontier models and publishing accurate, defensible leaderboard results.
- Develop failure-analysis tools that explain where and why models fail and link patterns to the relevant steps.
- Build dataset views, registries, and versioning features for benchmark discovery and management.
- Create onboarding, roles, key management, and usage views that enable customer self-service.
- Participate in customer pilots and translate lab and enterprise needs into the product roadmap.
Requirements
- Bachelor’s degree in Computer Science or a related field.
- Strong full-stack skills using a modern backend language such as Python, Go, or TypeScript and a frontend framework such as React.
- Track record of owning product features end to end, from ideation through production.
- Experience building data-heavy products with data models, APIs, and views over large volumes of results.
- Strong product sense and ability to focus on user needs.
- 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 is preferred.
- Startup experience or experience building B2B developer products is preferred.
Benefits
- Bi-annual performance bonus structure and equity grant.
- Relocation and housing assistance, plus a monthly meal stipend.
- Free Equinox membership and monthly laundry and personal wellness reimbursements.
- Health, dental, and vision insurance.
- In-person work five days per week in the San Francisco, NYC, or London office.
Tech Stack
Categories
About Mercor
Mercor builds an expert-powered platform that trains, evaluates, and deploys AI systems for AI labs and enterprises. It operates APEX to assess model performance on economically valuable tasks, and provides services such as custom AI agents and teams of vetted domain experts who encode organizational knowledge into AI. Founded in 2023 and headquartered in San Francisco, it is privately held and works with frontier AI labs and enterprise clients requiring strict data isolation.