Member of technical staff - Agent

Key Responsibilities

• Research & Leadership: Design and develop new agents, proposing new research directions, e.g., combining state-of-the-art RL with foundation models (LLMs/VLMs).
• Algorithm & Systems Design: Design, implement, and scale complex, high-performance systems for training large-scale agents. This includes both the foundational infrastructure and the novel algorithms, reward models, and sophisticated training environments.
• Research-to-Production: Collaborate closely with researchers and engineers to implement, test, and productionize new agent logics, learning algorithms, and system architectures.
• Evaluation & Reliability: Create, manage, and scale massive benchmarks and evaluation systems to rigorously track agent capabilities. You will own system reliability, scalability, and observability for our entire research infrastructure.
• Mentorship & Standards: Mentor and guide other engineers and researchers on the team, fostering technical excellence. You will establish and enforce engineering standards, tooling, and best practices for both code and research design.
• Innovation: Conduct thorough code and design reviews, champion technical innovation, and proactively address technical debt to accelerate the R&D lifecycle.

Requirements

• Technical Skills:
• Senior Experience: Previous demonstrable role(s) as a Staff, Principal, or Senior Engineer (or equivalent Research Scientist) in a Frontier AI Lab with a proven track record of leading complex, end-to-end AI/ML projects from conception to production.
• Education / Publication: 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.
• Core Expertise: Deep theoretical and practical expertise in Agentic AI and proven experience building, scaling, and shipping solutions involving foundation models (LLMs/VLMs).
• Soft Skills:
• Collaborative: Enjoys collaboration and thrives in a teamwork-oriented, fast-paced research environment.
• High-Impact Communicator: Possesses impactful communication skills, with the ability to bridge the gap between research and engineering and articulate complex ideas clearly.
• Mission-Driven: Genuinely eager to explore and solve the new engineering and research challenges at the frontier of agentic AI.
• Bonus Skills:
• Practical experience applying Reinforcement Learning to systems built on Large Language Models (LLMs).
• Experience with distributed systems or cloud computing, preferably in AWS.
• Familiarity with building complex simulation environments for agent training.
• Experience with LLM training or fine-tuning.
• Experience developing large-scale evaluation and benchmarking systems for AI models.
• Experience in an agentic framework (e.g., LangChain, AutoGen, CrewAI, OpenAI SDK).
• Expertise in system architecture, instrumentation, observability, and monitoring for complex, high-performance systems.

Location

• Paris or London.
• This role is hybrid, and you are expected to be in the office 3 days a week on average.
• Please expect some travel between offices on a reasonable cadence (e.g., every 4-6 weeks).