about 4 hours ago
Base Salary
$220k - $600k/yr
Responsibilities
- Build backend and infrastructure systems for Deeptune’s reinforcement-learning environments.
- Create high-fidelity simulations and training gyms for AI agents.
- Build partnerships with leading AI labs and enterprises.
- Improve frontier model quality through data, evaluation, and systems work.
- Contribute to reinforcement learning with verifiable rewards, rubric-based reward modeling, and pipelines that convert human demonstrations into training-ready environments.
- Set technical direction, drive outcomes, remain hands-on, and lead and coach engineers.
Requirements
- 4–10 years of engineering experience.
- At least 2–3 years of experience in the unspecified additional area described in the posting.
- Strong background building scalable systems.
- Comfort with core ML and LLM concepts, including post-training, evaluation metrics, and reward modeling.
- Experience leading in ambiguous, fast-moving environments with sound technical judgment.
- Proven ability to coach engineers and drive execution.
- A founding-engineer, founder, or major-impact background at a top-tier company and readiness to join an early-stage team.
- Interest in agentic AI and motivation to build frontier technology.
Benefits
- In-person work five days per week from offices in San Francisco, New York City, or London, with the role based at One World Trade.
- Relocation assistance for moving to the New York metropolitan area.
- Housing assistance for 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
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.