Post-Training Research Scientist

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.

Requirements

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.

Qualifications

Master’s or PhD in Machine Learning or a related field.

Experience with large-scale machine learning systems and models.

Strong publication record in top-tier conferences and journals.

Excellent communication and collaboration skills.

Skills

Deep understanding of machine learning theory and practice.

Experience with distributed systems and large-scale data processing.

Ability to design and execute rigorous experiments.

Strong problem-solving and critical thinking skills.

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.