2 months ago
Base Salary
$220k - $600k/yr
Responsibilities
- Build backend and infrastructure systems for Deeptune’s reinforcement-learning environments and AI-agent training gyms.
- Develop data, evaluation, reward-modeling, and systems pipelines that turn human demonstrations into training-ready environments.
- Partner directly with leading AI labs and enterprises.
- Contribute hands-on to improving frontier model quality.
- Set direction, drive outcomes, stay hands-on, and lead execution in an ambiguous early-stage environment.
- Coach engineers and apply sound technical judgment to complex problems.
Requirements
- 4–10 years of engineering experience.
- 2–3+ years of experience with an unspecified area in the posting.
- Strong background building scalable systems.
- Comfort with core ML and LLM concepts including post-training, evaluation metrics, and reward modeling.
- Ability to lead in ambiguous, fast-moving environments with sound technical judgment.
- Proven ability to coach engineers and drive execution.
- Experience as a founding engineer, company founder, or high-impact contributor at a top-tier company.
- Strong ownership mindset, pragmatic decision-making, and interest in agentic AI.
- Willingness to work in person five days per week from the office.
Benefits
- In-person work five days per week from the San Francisco, New York City, or London offices, with this role based at One World Trade.
- Relocation assistance for moving to the New York metropolitan area.
- Housing assistance for employees living within 0.5 miles of the office.
- Monthly meal stipend.
- Free Equinox membership.
- Monthly laundry reimbursement.
- Monthly personal wellness reimbursement.
- Health, dental, and vision insurance.
- 401(k) with company match.
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.