Member of Technical Staff, Deeptune Environments

Job summary

Responsibilities

You'll build the systems our high-fidelity simulation environments run on, the APIs and tool interfaces agents interact with, the grading layer that decides whether an agent actually succeeded, the pipelines that turn raw human demonstrations into training-ready environments, and the orchestration…

• 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…
• Turn messy human data into clean, reproducible training environments.
• Care about reliability and speed as much as correctness.
• Own the interface with labs and researchers: translate a research goal into a system that exists next week.

What they're looking for

• 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…
• Strong generalist with systems depth. We primarily use Python and seek engineers who are fluent in at least one language.
• 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…
• Thrives in ambiguity. You scope your own work, make pragmatic calls, and ship without a spec handed to you.
• Ability to raise the bar around you. Coaching engineers and driving execution, while staying in the code

Tech stack

• Python