Baseten

Post-Training Applied Researcher

San Francisco, Remote. Posted a month ago

The role

You will post-train open-source models to outperform frontier closed models on specialized tasks. You will build reward functions, environments, eval harnesses, and training pipelines using complex, domain-specific datasets.

What you will do

  • Design and run post-training pipelines including SFT, GRPO, DPO, RLVR, reward function engineering, and synthetic data generation.
  • Build task-specific training environments and evals for domains like healthcare, code generation, and legal.
  • Work directly with customers to translate production data into training signal.
  • Run and analyze training experiments end-to-end.
  • Publish findings at top venues and contribute to Baseten's open-source training libraries.

Required qualifications

  • Hands-on experience training LLMs with reinforcement learning.
  • Demonstrated understanding of GRPO or PPO including group advantage computation, clipped objectives, and KL penalty design.
  • Strong intuition for reward engineering.
  • Experience building multi-turn agent environments with tool use.
  • Comfort working across the full pipeline from dataset construction through training, evaluation, and deployment.
  • Experience with production ML systems.

Nice to have

  • Preference for candidates who have closed a training–inference loop where production data feeds back into model improvement
  • Experience with RL training frameworks
  • Publications at NeurIPS, ICML, ICLR, focused on RL for LLMs, reward modeling, or alignment

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

About the company

Baseten powers mission-critical inference for AI companies by uniting applied AI research, flexible infrastructure, and seamless developer tooling. The company recently raised a $1.5B Series F.