Applied Research - Evals & Data

Highlights

• Design next-gen AI agents tackling real customer workflows at scale.
• Build eval pipelines shaping how frontier models are aligned and deployed.
• Prototype agents and harnesses side-by-side with customers in the field.

What they offer

• Equity incentives
• Flexible work (remote or San Francisco)
• Visa sponsorship & relocation support
• Professional development budget
• Team off-sites & conference attendance

Ideal candidate

Customer-obsessed ML engineer excited by RL and evals who loves prototyping agents in the field and turning real-world feedback into better reasoning and reliability.

Requirements

• Strong background in machine learning engineering, with experience in post-training, RL, or large-scale model alignment
• Experience with applied data workflows and evaluation frameworks for large models or agents
• Deep expertise in distributed training/inference frameworks
• Experience deploying containerized systems at scale
• Track record of research contributions in ML/RL
• Passion for advancing reasoning, measurement, and practical agentic AI systems