Post-Training Research Scientist

BaseTen Inc.

Job Overview

Location

San Francisco

Job Type

Full-time

Full Job Description

📋 Description

• As a Post-Training Research Scientist at BaseTen Inc., you will work at the cutting edge of AI research, focusing on post-training methodologies and performant inference to advance the capabilities of large language models in production environments. Your work will directly impact how frontier AI companies like Cursor, Notion, and OpenEvidence deploy and scale their models, making this role pivotal in shaping the future of AI infrastructure.
• You will define and pursue a dual-focused research agenda: one-third dedicated to exploratory, foundational research in areas such as model learning, alignment, and architectural efficiency, and two-thirds devoted to solving urgent, real-world training and inference challenges faced by BaseTen’s platform and its high-growth AI customers. This balance ensures your work advances both scientific understanding and tangible product innovation.
• Day to day, you will design and execute large-scale experiments involving multi-node systems and models exceeding 1T parameters, rigorously testing hypotheses through empirical validation. You will collaborate closely with research engineering and infrastructure teams to translate insights into production-ready systems, ensuring research outcomes are not only publishable but also deployable at scale.
• You will author and publish original research at premier machine learning conferences including NeurIPS, ICML, and ICLR, helping establish BaseTen as a recognized leader in applied AI research. Your publications will contribute to the broader scientific community while reinforcing the company’s technical credibility and innovation profile.
• In addition to individual research, you will mentor junior researchers, foster a culture of scientific rigor and creativity, and help shape the long-term technical direction of BaseTen’s growing research organization as it scales to meet increasing demand from AI-driven enterprises.
• The team operates in a fast-paced, startup-driven environment where research is tightly coupled to product impact, with timelines measured in months rather than years. You will engage with some of the most innovative AI companies in the world, gaining exposure to diverse model architectures, deployment patterns, and real-world constraints that inform both research and infrastructure decisions.
• Through this role, you will deepen your expertise in post-training techniques such as distillation, alignment, and efficient inference, while developing strong judgment in problem selection — distinguishing research that improves benchmarks from research that transforms how AI systems are built and operated.

🎯 Requirements

• PhD or equivalent research depth in machine learning, with a strong record of first-author publications at top-tier venues such as NeurIPS, ICML, or ICLR
• Demonstrated ability to bridge theory, implementation, and empirical validation — moving fluidly between conceptual work, experimentation, and systems-level execution
• Proven judgment in research problem selection, with the ability to identify questions that advance fundamental understanding or drive meaningful changes in system design
• Willingness and aptitude to thrive in a dynamic startup environment where research priorities evolve rapidly and are closely aligned with product and customer needs

🏖️ Benefits

• Competitive compensation package including meaningful equity participation in a fast-growing AI infrastructure company
• 100% employer-paid medical, dental, and vision insurance for employees and their dependents
• Generous paid time off policy, including a company-wide Winter Break (offices closed from Christmas Eve to New Year’s Day)
• Paid parental leave to support growing families
• Company-facilitated 401(k) retirement plan with administrative support
• Unique exposure to a diverse portfolio of cutting-edge ML startups, offering exceptional learning, collaboration, and networking opportunities

Skills & Technologies

Node.js

Apache Spark

Onsite

Degree Required

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BaseTen Inc.

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About BaseTen Inc.

BaseTen provides a serverless, GPU-accelerated platform that lets machine-learning teams deploy, scale and monitor custom models behind autoscaling inference endpoints. The service abstracts infrastructure management, supports PyTorch, TensorFlow and Hugging Face artifacts, and offers built-in observability, A/B testing and fine-tuning. Customers integrate via REST or GraphQL APIs and pay only for compute used. Founded in 2019 and headquartered in San Francisco, BaseTen targets data scientists and product teams seeking production-grade ML serving without Kubernetes complexity.

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