Research Engineer - Reinforcement Learning
You will lead and participate in research on large-scale synthetic data generation and orchestration. You will optimize AI inference performance, cost, and resource utilization, develop open-source synthetic data and distributed reinforcement learning frameworks, publish research, and communicate technical outcomes through accessible technical writing.
Responsibilities
- Lead and participate in research on synthetic data generation
- Build a large-scale synthetic data generation pipeline and orchestration solution
- Optimize AI inference performance, cost, and resource utilization
- Develop open-source synthetic data generation libraries and frameworks
- Develop distributed reinforcement learning frameworks
- Publish research at top-tier AI conferences
- Explain technical project outcomes through accessible technical blogs
- Track advances in AI/ML infrastructure, tools, and synthetic data research
- Identify opportunities to improve platform capabilities and user experience
Requirements
- AI/ML engineering experience
- End-to-end large-scale model inference or training pipelines
- Distributed inference
- vLLM
- SGLang
- MLOps
- Model versioning
- Experiment tracking
- CI/CD pipelines
Benefits
- Equity incentives
- Flexible work arrangements
- Remote or in-person work options
- Visa sponsorship
- Relocation assistance
- Quarterly team off-sites
- Hackathons
- Conferences
- Learning opportunities