Research Scientist
San Francisco$200k - $335kFull-timePosted 11mo ago
About the role
Design, implement, and optimize large-scale training infrastructure for frontier reinforcement learning, enabling reliable, fast, and scalable training and production deployment of RL models for enterprise partners.
Responsibilities
- Design and optimize our RL training and inference pipelines across large GPU clusters
- Build tooling and observability that lets researchers and customers inspect, profile, and debug training runs
- Implement systems with an eye toward how they affect ML (low precision numerics, distributed training edge cases, etc.)
- Partner with researchers to bring frontier post-training capabilities into production deployments
Qualifications
- Experience programming with and managing training jobs on large-scale GPU systems
- Fearlessness and curiosity to understand all levels of the training stack
- Bias toward fast implementation, paired with a high bar for reliability and efficiency
- Familiarity with open-weights models (architecture and inference)
- Background in reinforcement learning or integration of inference with RL training loops
Skills
Required:GPU-based large-scale trainingReinforcement learning
Nice to have:Distributed training
Benefits
- Competitive compensation and equity
- 100% employer-paid health insurance coverage for you and your family
- Unlimited PTO
- Paid parental leave
- Daily lunches and dinners
- Transportation and relocation support
- 5% 401k match
Last updated Sep 30, 2026. Interested? Apply on the company site.
About Applied Compute
Specific Intelligence for Your Business
Specific Intelligence for Your Business
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