Software Engineer, Machine Learning

Навыки

• Elasticsearch
• Kafka
• Kubernetes
• Machine Learning
• PostgreSQL
• Python
• RAG

О компании и продукте

• Mercor's mission is to organize human intelligence to power the AI economy. We're a leading AI data company, building the layer between human expertise and frontier models. Millions of domain experts on the platform are paid over $4 million per day to train frontier AI models. Mercor's APEX benchmark family measures AI's real-world impact on professional work. Mercor Enterprise brings this same infrastructure to Fortune 500 companies: helping companies capture how their best people actually work, translating that expertise directly back into agents.
• 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.
• 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.

Задачи

• 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, structured attributes, and behavioral signals
• Optimize ranking toward long-term hiring outcomes under delayed and incomplete labels
• Design models that balance marketplace objectives such as fill rate, quality, speed, and conversion
• Build systems for candidate allocation, opportunity routing, and liquidity optimization
• Develop evaluation and experimentation frameworks that connect model performance to business results

Требования

• Strong track record of shipping ML systems into production
• Experience with ranking, recommendation, search, matching, or marketplace problems
• Good judgment on model design, objective functions, evaluation, and tradeoffs
• Comfort working across the full applied ML stack: data, features, training, inference, and iteration
• Strong engineering fundamentals and a bias toward simple, robust systems

Условия

• 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)
• $1.5K monthly stipend for meals
• Free Equinox membership
• $200 monthly laundry reimbursement
• $200 monthly personal wellness reimbursement
• Health, Dental, Vision insurance

Паспорт вакансии

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