AI Scientist - Agentic Engineering

Alongside this, you'll help shape the agent architectures and harness that let these models operate reliably inside multi-step engineering workflows, not just answer isolated questions.

You'll work closely with domain experts across CAE and EDA or other domains to ground this work in how engineers actually work, and with the broader research team to translate that domain grounding into training signal and evaluation benchmarks that measure genuine task competence.

This is early-stage work, and that's the point: you'd be joining at the foundation, shaping the data, verifiers, and agent scaffolding that decide whether these systems become reliable or stay demo-grade. There's no inherited playbook, you'll help define what good looks like, and your work will set the direction the team builds on rather than extend an existing one. What you will do

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

What we'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

Low-ego, collaborative, and eager to learn at the intersection of engineering and ML

It would be great if you

Have experience building or fine-tuning agentic systems (tool use, multi-step planning, agent orchestration frameworks)

Have experience with reward modeling, RLHF/RLAIF/RLVR, or preference-based training

Have industrial or academic experience with CAE or EDA tools (e.g. SolidWorks, CATIA, Fluent, Abaqus, LS-DYNA, STAR-CCM+, Cadence/Synopsys/Siemens EDA tools)

Have contributed to a large open-source or industry codebase

Have publications in engineering and ML venues (NeurIPS, ICLR, JFM, AIAA, etc.)

What We Offer

We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks.

For the most up-to-date details on benefits available in your location, please refer to our Benefits page .

Privacy Policy

Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy .

Find more English Speaking Jobs in France on Arbeitnow