Research Engineer – RL Infra
Prime Intellect
full-time
Posted on:
Location Type: Remote
Location: United States
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About the role
- Design and build scalable RL training infrastructure — async trainers, environment orchestration, reward pipelines — across large GPU clusters.
- Optimize performance, cost, and resource utilization of RL workloads using state-of-the-art compute and memory optimization techniques.
- Contribute to our open-source libraries and frameworks for distributed RL training.
- Publish research at top-tier venues (ICML, NeurIPS).
- Write clear, approachable technical content distilling complex systems work for customers and the broader community.
- Stay current with advances in RL systems, distributed training, and ML infrastructure, and proactively identify opportunities to enhance our platform.
Requirements
- Strong background in ML engineering, with hands-on experience building and scaling RL or large model training pipelines end-to-end.
- Deep expertise in distributed training techniques and frameworks (e.g., PyTorch Distributed, DeepSpeed, vLLM, Ray) including data, tensor, and pipeline parallelism.
- Experience with RL-specific infrastructure: environment management, rollout workers, reward model serving, or online/async training loops.
- Solid understanding of MLOps best practices — experiment tracking, model versioning, CI/CD.
- Passion for advancing open, scalable RL infrastructure and democratizing access to frontier AI capabilities.
- If you're not familiar with all of the above but feel you can contribute to our mission and you're a high-energy person, get familiar with these resources (here, here, and here) and please reach out!
Benefits
- Competitive compensation including equity, aligning your success with Prime Intellect's growth and impact.
- Flexible work arrangements — remote or in-person at our San Francisco office.
- Visa sponsorship and relocation assistance for international candidates.
- Quarterly team offsites, hackathons, conferences, and learning opportunities.
- A talented, hard-working, mission-driven team united by a shared passion for accelerating AI research.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
reinforcement learningdistributed trainingMLOpsPyTorch DistributedDeepSpeedvLLMRayexperiment trackingmodel versioningCI/CD
Soft Skills
communicationtechnical writingcollaborationproblem-solvingadaptabilitypassion for open-sourceproactive identification of opportunitiescustomer-focusedhigh-energyapproachability