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AI Scientist - Agentic Engineering

Mistral AIParisScience
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Salary
Not listed
Job type
Full-time
Work mode
Remote
Posted
4 Sept 2026
Status
Open · checked 7d ago

About this role

Role Overview

The AI Scientist - Agentic Engineering role at Mistral AI is an early-stage position based in Paris with remote work options, suited for machine learning experts with practical engineering workflow experience. Professionals in this role develop pre and post-training data and agent architectures to help frontier large language models reason about and execute complex engineering tasks.

Key Responsibilities

Create pretraining, supervised fine-tuning, and reinforcement learning datasets tailored for computer-aided engineering, computer-aided design, and semiconductor electronic design automation tasks.
Establish verification methods and evaluation metrics to accurately measure the correctness and quality of engineering outputs beyond surface-level plausibility.
Develop and optimize agent architectures and harnesses to enable models to plan, execute tool calls, recover from errors, and manage multi-step engineering workflows.
Construct evaluation benchmarks and diagnostic tools to pinpoint model failures and trace them back to data limitations, reward designs, or agent scaffolding issues.
Partner with domain specialists in CAE and EDA to identify high-value engineering workflows to target.
Share findings and methodologies with the broader research team to contribute to Mistral AI's overall pre and post-training initiatives.

Requirements

Fluent English communication skills with the ability to articulate complex technical machine learning and engineering concepts to diverse audiences.
Extensive, hands-on machine learning expertise with a strong focus on large language model development.
Proven practical experience running, debugging, and validating genuine engineering workflows within CAD, CAE, semiconductor simulation, or EDA.
Proficiency in writing clean, readable Python code alongside comfort operating in Linux and high-performance computing environments.
A self-directed work ethic with the ability to make progress without relying on detailed roadmaps.
A collaborative, low-ego mindset paired with a strong eagerness to learn at the intersection of machine learning and engineering.

Nice to Have

Prior experience building or fine-tuning agentic systems, including tool use, multi-step planning, and agent orchestration frameworks.
Background in reward modeling, preference-based training, or reinforcement learning techniques such as RLHF, RLAIF, or RLVR.
Industrial or academic familiarity with CAE or EDA tools, such as SolidWorks, CATIA, Fluent, Abaqus, LS-DYNA, STAR-CCM+, or commercial EDA software.
History of contributions to large open-source or industry codebases.
Published research in relevant engineering and machine learning venues like NeurIPS, ICLR, JFM, or AIAA.

Skills and Tools

Python
Large Language Models (LLMs)
Linux and HPC environments
CAD, CAE, and EDA tools
Agentic systems and reinforcement learning frameworks

About the Company

Mistral AI delivers comprehensive artificial intelligence solutions ranging from frontier models to developer tools, applications, and compute power. The organization collaborates with enterprises operating in demanding sectors such as finance, manufacturing, defense, healthcare, and the public sector to build customized AI systems. Operating with a distributed workforce across Europe, North America, Asia, and the Middle East, Mistral AI maintains a dynamic, collaborative, and low-ego culture driven by innovation.

How to Apply

Interested candidates should apply directly on the official company careers page.

Skills and tech stack

PythonLLM

Questions candidates ask

Where is the AI Scientist - Agentic Engineering position located?

The role is based in Paris with remote work possibilities, as Mistral AI's teams are distributed across Europe, North America, Asia, and the Middle East.

What are the core responsibilities of this AI Scientist role?

The core responsibilities involve building pre and post-training data, designing verifiers, and shaping agent architectures and harnesses to help frontier LLMs execute engineering tasks like CAE and EDA.

What technical background is required for applicants?

Applicants need deep, hands-on machine learning expertise with LLMs, demonstrated experience with real engineering workflows in CAD, CAE, semiconductor simulation, or EDA, and proficiency in Python and Linux/HPC environments.

Are there any preferred qualifications for this position?

Preferred qualifications include experience with agentic systems, reinforcement learning methods, industrial CAE or EDA tools, open-source code contributions, and academic publications in machine learning or engineering venues.

How should I apply for this job?

Candidates should apply directly on the official company careers page.

Ready to apply?

The application is on the official Mistral AI careers page.

Apply on company site