- Paris, Île-de-France, France
ML Engineer focused on LLMs, agents, and reinforcement learning for autonomous supply chain decision-making.
Responsibilities
- Design and implement LLM-powered agent environments for supply chain decision-making
- Fine-tune, adapt, and evaluate LLMs for domain-specific reasoning and decision support
- Design, test, and iterate on reward functions that capture the behaviors we want from LLM agents
- Review LLM traces and rollouts to understand model reasoning, failure modes, reward hacking, and shortcut behaviour
- Identify when an LLM is exploiting the reward function, escaping the intended RL process, or optimizing for proxy metrics instead of the real objective
Requirements
- Nice to have: human-in-the-loop ML systems
- Nice to have: evaluation frameworks for open-ended tasks
- Nice to have: supply chain
- Nice to have: logistics
- Nice to have: operations domains