Applied Researcher - Open-Source AI Platform

Prime Intellect AI; San Francisco (CA); Remote; USD 150,000 - 300,000; Full time

Benefits offered by this job

Equity incentives

Remote work options

Visa sponsorship & relocation

Professional development budget

Team off-sites & conferences

Job summary

Prime Intellect is seeking a Research Engineer to translate emerging frontier research into open-source and product-ready systems. You will collaborate closely with engineering and applied researchers to shape interfaces, build core RL and evaluation tooling, and expose reusable components to the broader community.

You will own critical open-source ML tooling, drive experiments, and contribute artifacts others can run and extend.

Qualifications

• Ownership of open-source ML or developer-tool systems.
• Hands-on experience building and debugging model-training, post-training, agent, evaluation loops.
• Strong experimental judgment: meaningful baselines, trace inspection, fault attribution.
• Strong Python and ability to build runnable artifacts that others can run, inspect, and extend.
• Comfort owning ambiguous problems and keeping partners updated.

Responsibilities

• Own important open-source RL, environment, evaluation, and agent systems.
• Develop researcher-facing features in our training platform with engineering and design.
• Create APIs, examples, reference implementations, and explanations exposing useful abstractions.
• Collaborate with research users and external contributors to improve interfaces and artifacts.
• Work with customers, users, and partners to advance the research-to-product path.

Skills

Python

Open-source ML

Research engineering

Experimental judgment

Documentation

Tools

PyTorch

Git

Job description

Prime Intellect is seeking a Research Engineer to translate emerging frontier research into open-source and product-ready systems. You will collaborate closely with engineering and applied researchers to shape interfaces, build core RL and evaluation tooling, and expose reusable components to the broader community.

You will own critical open-source ML tooling, drive experiments, and contribute artifacts others can run and extend.