Post-Training Research Scientist
$210k - $285k • Remote • San Francisco • FullTime
Posted 7mo ago
Job Location
San Francisco
Tech Stack
Remote Work Policy
Fully remote
Employment Type
FullTime
Categories
AI Research Engineer
About the job
Baseten powers mission-critical inference for leading AI companies, enabling them to bring cutting-edge models into production. We are seeking a Post-Training Research Scientist to join our team and pursue open problems at the intersection of post-training methodology and performant inference. This role involves both foundational research to deepen our understanding of model learning and alignment, and applied research to solve concrete problems for Baseten's platform and its rapidly growing AI customers. You will design and execute rigorous experiments, potentially at a large scale, and collaborate with research engineering to translate findings into production systems. We value sharp research taste, creative problem selection, and the ability to validate research with real-world applications.
Responsibilities
- Define and pursue a research agenda spanning foundational and applied work, connected to Baseten's platform and customer needs.
- Design and execute rigorous experiments, frequently at meaningful scale (multi-node, trillion parameter models).
- Collaborate with customers to translate domain-specific requirements into research problems.
- Publish research at top venues (NeurIPS, ICML, ICLR) and establish Baseten's research presence.
- Bridge research findings with inference production systems by collaborating with model performance and training infrastructure teams.
- Mentor junior researchers and shape the technical direction of the research organization.
Requirements
- Master's or PhD research depth in machine learning, with first-author publications at top venues.
- Demonstrated ability to move from theory through implementation to empirical results.
- Strong judgment about problem selection and the ability to distinguish impactful research.
- Willingness to operate in a startup environment where research often informs product decisions with shorter timelines.
- Background spanning multiple research areas (e.g., interpretability and RL, or 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 (U.S. only).
- Flexible PTO policy including company-wide Winter Break.
- Paid parental leave.
- Fertility and family-building stipend through Carrot.
- Company-facilitated 401(k) (U.S. only).
- Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities.