Responsibilities
- Design and develop new agents, proposing new research directions, e.g., combining state of the art RL with foundation models (LLMs/VLMs).
- Design, implement, and scale complex, high performance systems for training large scale agents.
- Collaborate closely with researchers and engineers to implement, test, and productionize new agent logics, learning algorithms, and system architectures.
- Create, manage, and scale massive benchmarks and evaluation systems to rigorously track agent capabilities.
- Mentor and guide other engineers and researchers on the team, fostering technical excellence.
- Conduct thorough code and design reviews, champion technical innovation, and proactively address technical debt to accelerate the R&D lifecycle.
Requirements
- Previous demonstrable role(s) as a Staff, Principal, or Senior Engineer (or equivalent Research Scientist) in a Frontier AI Lab.
- Preferably PhD (or equivalent research experience) in Machine Learning, Computer Science, or a related field, preferably with a strong publication record (e.g., NeurIPS, ICML, ICLR) in Computer Science.
- Deep theoretical and practical expertise in Agentic AI and proven experience building, scaling, and shipping solutions involving foundation models (LLMs/VLMs).
- Enjoys collaboration and thrives in a teamwork oriented, fast paced research environment.
- Possesses impactful communication skills, with the ability to bridge the gap between research and engineering and articulate complex ideas clearly.
- Genuinely eager to explore and solve the new engineering and research challenges at the frontier of agentic AI.
Core Competencies
Demonstrates deep expertise in Agentic AI, with a strong focus on designing and developing high-performance systems for large-scale agents. Proven ability to mentor teams, conduct rigorous evaluations, and bridge research with engineering practices.