AI Scientist - Agentic Engineering

Job summary

Responsibilities

Mistral is looking for AI Scientists with deep ML expertise and hands-on engineering experience to expand what our agentic tools can do across the engineering lifecycle — CAE (CFD, FEA, etc.) and EDA/Semi.

• Design pretraining, SFT, and RL data for engineering tasks across CAD, CAE, and semiconductor/EDA
• Define verifiers and evaluation criteria that capture what "correct" and "high-quality" actually mean for each engineering task, beyond surface-level plausibility
• Design and improve agent architectures and harnesses: how models plan, call tools, recover from errors, and chain steps together across long-horizon engineering workflows
• Build evaluation benchmarks and diagnostic tooling to identify where models fail on engineering tasks, and trace those failures back to gaps in data, reward design, or agent…
• Collaborate with domain experts across CAE and EDA or other domains (and the science and solutions teams more broadly) to identify which engineering workflows are highest-value…

What they're looking for

• Fluent English with excellent communication skills, able to explain technical ML and engineering concepts to both engineering and non-technical audiences
• Deep, hands-on machine learning expertise, particularly LLM development
• Demonstrated experience running, debugging, and validating real engineering workflows in at least one of CAD, CAE, semiconductor simulation, or EDA
• You write clean, readable Python code and are comfortable in Linux/HPC environments
• Self-directed, you don't need detailed roadmaps to make progress

Tech stack

• Python