Machine Learning Engineer, Marketplace

🇺🇸 San Francisco, California
$1K - $5K Annual
Posted 1 week ago
Expires June 9, 2026

ABOUT MERCOR

Mercor is defining the future of work. We partner with leading AI labs and enterprises to provide the human intelligence essential to AI development.

Our vast talent network trains frontier AI models in the same way teachers teach students: by sharing knowledge, experience, and context that can't be captured in code alone. Today, more than 30,000 experts in our network collectively earn over $2 million a day.

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

As a Machine Learning Engineer on the Marketplace team, you will build the models and decision systems that power Mercor’s hiring engine. This includes search and ranking, candidate-job matching, marketplace recommendations, personalization, and allocation decisions across a rapidly growing talent network.

This is an applied ML role with direct product and revenue impact. You will work on problems shaped by real marketplace constraints: sparse and delayed labels, cold start, noisy feedback, heterogeneous supply and demand, and the need to optimize across speed, quality, and conversion simultaneously.

What You’ll Build

• Ranking and matching systems that determine which candidates and opportunities are surfaced
• Models for recommendation, personalization, and marketplace optimization
• Retrieval, scoring, and decision pipelines operating at global scale
• Feedback loops that learn from downstream hiring outcomes, not just top-of-funnel engagement
• Real-time and batch inference systems embedded in product-critical workflows

Example Problems

• Improve candidate-job matching using embeddings, st...

More Jobs at Mercor