Responsibilities
- Develop and refine ML pipelines for agent behaviors using prompting, fine-tuning, retrieval-augmented generation, and reinforcement learning techniques.
- Prototype and experiment with novel agent reasoning, multi-step planning, and tool usage for complex, data-heavy domains.
- Run structured experiments to evaluate agent performance, optimize reasoning and retrieval, and translate findings into production-ready solutions.
- Build data pipelines and evaluation frameworks that support rapid iteration and deployment of new agent capabilities.
- Collaborate with orchestration and infra teams to ensure agent models are robust, scalable, and reliable in production.
Requirements
- Have 3+ years of experience building and analyzing ML systems, including data pipelines, and training frameworks.
- Have strong experience with LLMs, prompting, fine-tuning, and ML experimentation.
- Understand retrieval systems, vector databases, and reasoning techniques for large-scale text datasets.
- Enjoy blending research and engineering to push agent capabilities forward.
- Thrive in fast-paced environments where prototypes quickly evolve into production systems.
Benefits
- Competitive salary and equity, with 10 year exercise window for stock options
- Remote-first culture built on trust, autonomy, and high performance
- Team offsites for all of us to bond
- Take what you need vacation policy
- Top notch health, dental, and vision insurance subsidized by us
