Mercor
Member of Technical Staff, Deeptune Environments
New York City · Staff+
Sponsorship not specifiedDetected 67 days ago
PythonFull-Stack DevelopmentMachine LearningLLMsResearchMentoring
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About the role
- Your job is to make their ideas real: fast, correct, and reliable at scale.
- That means you should know enough about post-training, evals, and reward modeling to push back on a research spec productively.
- It does not mean you'll be training models.
Responsibilities
- Build the systems that build environments end-to-end: the simulated app or system, the agent-facing tool surface, the task definitions, and the verifiers that score them.
- Design and operate the backend infrastructure that runs environments at scale (containers, orchestration, queues, observability) - standard distributed-systems backend work, applied to a new domain.
- Own the interface with labs and researchers: translate a research goal into a system that exists next week.
- We care more about what you've built than how long you've been building it.
- Comfortable around ML/LLM concepts. Not an ML background, but enough working knowledge of post-training, evals, and reward modeling to partner with researchers and translate their specs into systems.
- Thrives in ambiguity. You scope your own work, make pragmatic calls, and ship without a spec handed to you.
- We build the systems that let researchers turn real-world tasks into training environments at scale.
Requirements
- 2+ years of full-stack / backend engineering, including at least 1 year at a startup, ideally as a founding engineer, an early engineer at a fast-growing venture, or a founder yourself
- Ability to raise the bar around you.
Benefits
- Bonus, not required: sandboxing or virtualization, browser and computer-use automation, CI/build systems, developer tooling.
- Deeptune Environments is a Mercor team building the platform and tooling that AI labs use to train agents through reinforcement learning.
Company info
- 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.
This listing is sourced directly from Mercor's careers page and normalized into a canonical job model.