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Baseten

Runs AI models for production software

Post-Training Applied Researcher

Natural Language Processing & LLMsConfirmed live in the last 24 hours
Full-timeSan Francisco, CA, USAHybrid

About the Job

Requirements

  • Hands-on experience training large language models with reinforcement learning, including understanding GRPO or PPO beyond recipe-level reproduction, group advantage computation, clipped objectives, and KL penalty design.
  • Strong intuition for reward engineering and the ability to distinguish between rewards that train effectively and rewards that will be exploited at scale.
  • Experience building multi-turn agent environments with tool use, beyond single-turn question-answering setups.
  • Comfort working across the full pipeline from dataset construction through training, evaluation, and deployment.
  • Experience with production machine learning systems.

Responsibilities

  • Design and run post-training pipelines, including supervised fine-tuning, GRPO, DPO, RLVR, reward function engineering, and synthetic data generation.
  • Build task-specific training environments and evaluations tailored to customer domains such as healthcare, code generation, and legal, spanning multi-turn tool use, sandboxed execution, and agentic workflows.
  • Work directly with customers to translate production data into training signal, design reward loops from real usage patterns, and handle distribution shift.
  • Run and analyze training experiments end-to-end, diagnosing reward hacking, importance sampling drift, and advantage estimation instabilities.
  • Publish findings at top venues and contribute to Baseten's open-source training libraries.

Desired Qualifications

  • Experience with reinforcement learning training frameworks.
  • Publications at NeurIPS, ICML, or ICLR focused on reinforcement learning for large language models, reward modeling, or alignment.
  • Experience closing a training–inference loop where production data feeds back into model improvement.

About the Company

Baseten

Runs AI models for production software

Baseten runs AI models for software companies that need fast, reliable responses inside their products, from text generation to speech and image processing. Its Inference Stack combines optimized model runtimes with infrastructure that deploys, serves, and monitors custom or open models in production. Teams package models with its open source Truss tool, while Model APIs let developers test ready-to-use models and Training runs jobs that adapt models to their own data. Customers pay for computing time or tokens processed, with negotiated plans for larger deployments and support needs. Baseten was founded in 2019 and is headquartered in San Francisco.

Company size
201-500
Company stage
Series F
Total funding
$2.1B
Headquarters
San Francisco, CA
Founded
2019

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