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Post-Training Research Scientist

baseten · San Francisco, California

Location
San Francisco, California, United States
Workplace
Hybrid
Employment
Full time
Level
Mid level
Posted
6 months ago

About this role

ABOUT BASETEN

Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. 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're growing quickly and recently raised our $1.5B 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.

THE ROLE

This role sits at the frontier of our research agenda. 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.

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.

We are looking for someone with sharp research taste and genuine creative instinct for problem selection. Someone who can identify questions that matter, design clean experiments to answer them, and push the state of the art. The environment here is not theoretical, but rather research that can be validated with eager customers who are serving billions of tokens a second.

RECENT RESEARCH

RESPONSIBILITIES

  • Define and pursue a research agenda spanning both foundational 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, trillion parameter models).

  • Work with customers to translate domain-specific requirements into research problems, where relevant to your agenda.

  • 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 inference production systems.

  • Mentor junior researchers and shape the technical direction of the research organization as it grows.

PREFERRED QUALIFICATIONS

  • 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 - 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)

  • Track record of open-source contributions or community building in ML research

OUR VIEW ON TALENT

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; PhDs working on the wrong-shaped problem at the right-shaped lab; operators who have been close to real systems long enough to see things credentialed researchers have never had to see. If you don’t have the traditional qualifications and are doing exceptional work, we’d love to chat.

BENEFITS

  • 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

  • Company-facilitated 401(k)

  • Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities.

Apply now to embark on a rewarding journey in shaping the future of AI! 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.

At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status.

We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).

As published by baseten. Applications are handled on their site.

Skills this posting mentions

Apache SparkArtificial IntelligenceResearch

About baseten

Inference is everything. Baseten is an AI infrastructure platform giving you the tooling, expertise, and hardware needed to bring great AI products to market - fast. Our proprietary Inference Stack utilizes the cutting-edge of performance research combined with highly performant and reliable infrastructure to give you out-of-the-box global availability with 99.99% of uptime.

All 66 openings at baseten

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Drop a resume or a LinkedIn URL. I rank the live openings against it, rewrite the resume and write a cover letter for the best of them, and fill in the employer's form when you press the button. You read, you decide what goes out.

  1. 01Drop your resume

    A PDF or a LinkedIn URL. About a minute, once.

  2. 02I rank the openings

    Every weekday morning, the live catalog scored against your history. Up to 20 worth your time, not two hundred links.

  3. 03Each one is written up

    Resume rewritten for the posting, a cover letter, a fit score. Press send, or let me fill in the form.

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