Machine Learning Research Scientist, Evaluations

📋 Description

• Analyze model behavior to identify and diagnose failure modes in frontier LLMs and Agents.
• Design and build benchmarks and evaluation methods for text and multimodal data.
• Apply post-training expertise (SFT, RLHF, reward modeling) to address observed failures.
• Publish research findings in top AI conferences and journals.

🎯 Requirements

• Ph.D. or Master's in CS, ML, AI, or related field.
• Deep understanding of DL, RL, and large-scale model fine-tuning.
• Experience with post-training techniques (RLHF, preference modeling, or instruction tuning) and LLM
• Strong written and verbal communication; published ML research.
• Customer-facing experience.

🎁 Benefits

• Compensation includes base salary, equity, and benefits.
• Health, dental, vision coverage; retirement benefits; learning stipend; generous PTO.
• Possible commuter stipend and other benefits as applicable.