2 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
We find the best experts in every professional domain and put their knowledge to work training frontier models. Through APEX, we measure whether those models can actually perform economically valuable work. We're also bringing that expertise to enterprises: deploying custom AI agents, staffing teams with vetted domain experts, and helping organizations encode their own knowledge into AI systems.