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Mistral AI

Open-weight LLMs and enterprise AI deployment

AI Scientist - Agentic Engineering

AI ResearchPosted on Nov 12
Full-timeNo salary listedRemote

About the Job

Requirements

  • Fluent English and the ability to explain technical machine-learning and engineering concepts to engineering and non-technical audiences.
  • Deep, hands-on machine-learning expertise, particularly in large language model development.
  • Demonstrated experience running, debugging, and validating real engineering workflows in at least one of CAD, CAE, semiconductor simulation, or EDA.
  • Ability to write clean, readable Python code and work comfortably in Linux/HPC environments.

Responsibilities

  • Design pretraining, supervised fine-tuning, and reinforcement-learning data for engineering tasks across CAD, CAE, and semiconductor/EDA.
  • Define verifiers and evaluation criteria that assess correctness and quality for engineering tasks beyond surface-level plausibility.
  • Design and improve agent architectures and harnesses for model planning, tool use, error recovery, and chaining steps across long-horizon engineering workflows.
  • Build evaluation benchmarks and diagnostic tooling to identify model failures on engineering tasks and trace failures to gaps in data, reward design, or agent scaffolding.
  • Collaborate with domain experts across CAE and EDA, and with science and solutions teams, to identify high-value engineering workflows to target.
  • Contribute to broader pretraining and post-training research, sharing findings and methodology across the science organization.

Desired Qualifications

  • Experience building or fine-tuning agentic systems, including tool use, multi-step planning, or agent orchestration frameworks.
  • Experience with reward modeling, RLHF, RLAIF, RLVR, or preference-based training.
  • Industrial or academic experience with CAE or EDA tools such as SolidWorks, CATIA, Fluent, Abaqus, LS-DYNA, STAR-CCM+, or Cadence, Synopsys, or Siemens EDA tools.
  • Contributions to a large open-source or industry codebase.
  • Publications in engineering and machine-learning venues such as NeurIPS, ICLR, JFM, or AIAA.

About the Company

Mistral AI

Open-weight LLMs and enterprise AI deployment

Mistral AI builds open-weight large language models and the tools to run them, along with inference infrastructure and enterprise products that let organizations deploy AI with control over data residency, customization, and the underlying stack. Its platform provides open-model architectures and a deployment stack for inference, governance, and integration that can run on‑premises or in the cloud. This openness and modular stack differentiate it from single-vendor hyperscalers by prioritizing data locality and flexibility. The company aims to enable reliable, customizable AI deployment at scale for businesses and public-sector customers across many countries.

Company size
1,001-5,000
Company stage
Series D
Total funding
$7.2B
Headquarters
Paris, France
Founded
2023

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