AI Scientist — Engineering LLMs & Agent Architectures

Mistral; Greater London; On-site; GBP 120,000 - 180,000; Full time

Benefits offered by this job

healthcare coverage

parental leave

retirement plans

relocation support

wellness programs

meal and transportation allowances

other location-specific perks

Job summary

Mistral is seeking AI Scientists with deep ML expertise to expand agentic tools for engineering tasks across CAD, CAE, and semiconductor/EDA. You will help build pretraining data and verifiers, shaping how models plan, execute, and learn in real engineering workflows.

Joining at the foundation, you will define what good looks like, craft data and scaffolding, and collaborate with domain experts to push toward reliable, scalable AI systems that can operate across multiple engineering domains.

Qualifications

• Fluent English with excellent communication skills.
• Deep, hands-on machine learning expertise, particularly LLM development.
• Demonstrated experience running, debugging, and validating real engineering workflows in 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.
• Low-ego, collaborative, and eager to learn at the intersection of engineering and ML.

Responsibilities

• 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 scaffolding.
• 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 to target next.
• Contribute to Mistral's broader pre and post-training research, sharing findings and methodology across the science organization.

Skills

Fluent English

LLM development

CAD/CAE/EDA experience

Python

Linux HPC

Self-directed

Collaborative mindset

Job description

Mistral is seeking AI Scientists with deep ML expertise to expand agentic tools for engineering tasks across CAD, CAE, and semiconductor/EDA. You will help build pretraining data and verifiers, shaping how models plan, execute, and learn in real engineering workflows.

Joining at the foundation, you will define what good looks like, craft data and scaffolding, and collaborate with domain experts to push toward reliable, scalable AI systems that can operate across multiple engineering domains.