Tech Stack
Responsibilities
- Build models and decision systems for Mercor’s hiring engine, including search, ranking, candidate-job matching, marketplace recommendations, personalization, and allocation.
- Design and implement ranking and matching systems, models for recommendation and personalization, and retrieval, scoring, and decision pipelines.
- Develop feedback loops that learn from downstream hiring outcomes and real-time/batch inference systems.
- Improve candidate-job matching using embeddings, structured attributes, and behavioral signals, and optimize ranking for long-term hiring outcomes.
- Develop evaluation and experimentation frameworks to connect model performance to business results and balance marketplace objectives like fill rate, quality, speed, and conversion.
Soft Skills
Machine Learning System Design
Benefits
- Health Insurance
- Dental
- Vision
- Equity
- Relocation Assistance
- Gym/Wellness
- Mental Health
Culture
Fast-PacedCross-Functional TeamsMission-Driven
Requirements
Regions: Gb, Us
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About mercor
Industry: ai
Size: enterprise
Mercor organizes human intelligence to power the AI economy by partnering with AI labs and enterprises, providing essential human intelligence for AI development through a vast talent network. The company is a profitable Series C firm valued at $10 billion, focused on creating a new category of work where expertise drives AI advancement.
View company profile →Compensation
Equity: Generous equity grant vested over 4 years
Bonus: Bi-annual performance bonus structure