3 months ago
Base Salary
$130k - $500k/yr
Responsibilities
- Build ranking and matching systems that determine which candidates and opportunities are surfaced.
- Develop recommendation, personalization, and marketplace optimization models.
- Build retrieval, scoring, and decision pipelines operating at global scale.
- Create feedback loops that learn from downstream hiring outcomes.
- Develop real-time and batch inference systems embedded in product-critical workflows.
- Improve matching with embeddings, structured attributes, and behavioral signals.
- Build evaluation and experimentation frameworks connecting model performance to business results.
Requirements
- Strong track record of shipping machine learning systems into production.
- Experience with ranking, recommendation, search, matching, or marketplace problems.
- Strong judgment in model design, objective functions, evaluation, and tradeoffs.
- Comfort working across data, features, training, inference, and iterative applied ML development.
- Strong engineering fundamentals and a preference for simple, robust systems.
Benefits
- Bi-annual performance bonus structure and equity grant.
- Health, dental, and vision insurance.
- Free Equinox membership.
- In-person work five days per week in San Francisco, New York City, or London offices.
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.