Post-Training Research Scientist
Conducts research on post-training methodologies and performant inference for AI models, balancing pure research with applied work for production systems. Requires PhD in ML with top publications and ability to design rigorous experiments at scale.
About the job
Recent Research
- Dense, on-policy or both?
- Repeated kv cache for long-running agents
- Distillation without the dark – replicating black-box on-policy distillation on Baseten
Responsibilities
- Define and pursue a research agenda spanning both pure and applied work, with the applied component connected to Baseten's platform and customer needs
- Design and execute rigorous experiments, frequently at meaningful scale (multi-node, 1T+ parameter models)
- Publish at top venues (NeurIPS, ICML, ICLR) and establish Baseten's research presence
- Collaborate with model performance and training infrastructure teams to bridge research findings and production systems
- Mentor junior researchers and shape the technical direction of the research organization as it grows
Qualifications
- PhD or equivalent research depth in machine learning, with first-author publications at top venues
- Demonstrated ability to move from theory through implementation to empirical results — not exclusively theoretical or exclusively engineering work
- Judgment about problem selection, the ability to distinguish research that advances a metric from research that changes how systems are built
- Willingness to operate in a startup environment where the majority of research informs product decisions, with timelines measured in months rather than years
Preferred Qualifications
- Experience with production ML systems and an understanding of the constraints that cause academic solutions to fail in deployment
- Background spanning multiple research areas (e.g., both interpretability and RL, or both systems and training methodology)
- Track record of open-source contributions or community building in ML research
Benefits
- Competitive compensation, including meaningful equity.
- 100% coverage of medical, dental, and vision insurance for employee and dependents
- Generous PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!)
- Paid parental leave
- Company-facilitated 401(k)
- Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities.
Skills
Machine Learning, Post-Training, Inference Optimization, Reinforcement Learning, Interpretability, Production Ml Systems, PyTorch, JAX, LLMs, Distributed Training
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