Baseten

Post-Training Research Scientist

San Francisco · Junior

Sponsorship not specifiedDetected 127 days ago

Node.jsMachine LearningSparkResearch

About the role

This role sits at the frontier of our research agenda.
A meaningful portion of your time will be dedicated to research that deepens our understanding of how models learn, alignment, and architectural efficiency - questions that may not have immediate product application.
The remainder will be directed toward research that solves concrete problems for Baseten's platform and customers, who are the fastest growing AI companies in the world like Cursor, Lovable, and Notion.

Design and execute rigorous experiments, frequently at meaningful scale (multi-node, trillion parameter models).
Collaborate with model performance and training infrastructure teams to bridge research findings and inference production systems.
We're growing quickly and recently raised our $1.5B Series F https://www.baseten.co/blog/announcing-our-series-f/, led by Altimeter Capital, Conviction Partners, and Spark Capital.
Join us and help build the platform engineers turn to to ship AI products.
You will pursue open problems at the intersection of post-training methodology and performant inference, and then collaborate with research engineering to translate findings into production systems.
Someone who can identify questions that matter, design clean experiments to answer them, and push the state of the art.

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
Background spanning multiple research areas (e.g., both interpretability and RL, or both systems and training methodology)
Many of the labs that exist today run a credentialist talent model.
Concentrate the most already-legible researchers, and assume the concentration compounds.
The best researchers in this field are very often not yet legible.
Research engineers who have spent years inside a production stack and developed insights no PhD program teaches

Competitive compensation, including meaningful equity.
100% coverage of medical, dental, and vision insurance for employee and dependents
Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!)
Paid parental leave
Fertility and family-building stipend through Carrot
Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities.
If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you.
By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production.

We are looking for someone with sharp research taste and genuine creative instinct for problem selection.
The environment here is not theoretical, but rather research that can be validated with eager customers who are serving billions of tokens a second.
Work with customers to translate domain-specific requirements into research problems, where relevant to your agenda.
At Baseten, we are committed to fostering a diverse and inclusive workplace.

This listing is sourced directly from Baseten's careers page and normalized into a canonical job model.