Mistral

Research Engineer - Cybersecurity (RL Environments) at Mistral (Paris, France)

Mistral· Paris, France·

Role details

Work type
Hybrid
Employment
Full-Time

Mistral at a glance

A French AI lab building open and frontier-grade large language models, with the full developer and enterprise stack around them.

Mistral is a French AI lab that builds open and frontier-grade large language models and sells the full stack around them: developer tooling, an agent studio, consumer and enterprise apps like Le Chat and Vibe, custom model training, and its own GPU compute. Its edge is deployment control, with open weights, EU hosting, and self-hosting for regulated and sovereign buyers.

$3B+ raised · latest: Series C · 1.7B euros · Sept 2025 · backed by ASML, Nvidia, Andreessen Horowitz, DST Global

Job description

About Mistral

Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited.

The Role

Cybersecurity is one of the areas where AI could do the most good — and one where the capability must be built with particular care. As a Research Engineer on this track, you'll push our models' capabilities in vulnerability discovery and remediation, security analysis, incident response, and across the offensive-to-defensive spectrum of cybersecurity, and it will be your job to develop that ability deliberately and safely. The work sits at the meeting point of research and engineering: you'll devise new approaches and be the one to implement them. Concretely, that means designing and building RL environments that reproduce realistic security scenarios, pipelines that generate synthetic training instances at scale, and experiments and evaluations that show what our models can actually do. Your results feed directly into the production training runs that shape our frontier models, in close collaboration with Mistral's researchers, engineers, and security specialists. Security specialists and ML engineers are both welcome here — what matters is that you can hold your own in both worlds, and are eager to go deeper on the one you know less.

What You Will Do

  • Design and implement RL environments simulating cybersecurity scenarios.
  • Build the pipelines and infrastructure that generate synthetic cybersecurity training instances at scale — thousands of scenarios, not one hand-crafted exercise.
  • Conduct experiments and evaluations of model capabilities on these environments, from quick prototypes to controlled benchmark runs.
  • Own the infrastructure behind the environments: containers, sandboxes, VMs, cloud deployments, and orchestration (Kubernetes), all managed as code.
  • Partner with researchers and security specialists across Mistral, distilling their domain expertise into reproducible environments and datasets.
  • Write clear, efficient code in Python and enforce strong software-design practices: testing, code review, CI/CD.

What We're Looking For

  • Hands-on expertise in offensive and/or defensive cybersecurity: vulnerability analysis, web/network/cloud security, secure coding practices, and SOC.
  • Strong software engineering skills: clean, reliable, well-tested code — not just exploit scripts.
  • Fluency in Python plus comfort reading lower-level languages (C/C++) for vulnerability analysis.
  • DevOps experience: Docker, Kubernetes, cloud deployments, sandboxed or simulated environments.
  • A pragmatic research-to-engineering mindset: ship a working first version, then refine and scale it.
  • Working knowledge of RL techniques and LLM training methodologies, or strong motivation to develop it.
  • Self-starter, low-ego, collaborative — comfortable working across research and engineering.

Nice-to-haves

  • CTF, cyber-range, or bug-bounty experience — as a player, challenge author, or platform builder.
  • A research background in cybersecurity, academic or industrial, or in another experimental discipline.
  • Prior experience building RL environments or large-scale ML training infrastructure.
  • Relevant open-source contributions and projects.

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.

Why work at Mistral

  • Culture: Flat structure, high ownership, low ego, and a "builders, not order takers" mentality. The company values audacity, speed, rigor, and customer centricity.
  • Remote/Hybrid/Office: Based in Paris (15 rue des Halles); relocation support and visa sponsorship offered. Specific remote/hybrid policy not detailed, but global team suggests flexibility.
  • Notable perks and benefits (from careers page):
    • 20 weeks paid parental leave for all birthing parents.
    • 100% employer-sponsored medical, dental, and vision coverage for employees and dependents.
    • 6% 401k match (US) / 5% pension contribution (UK).
    • Childcare support (reserved daycare seats or financial assistance).
    • Meal allowances and transportation support.
    • Fitness and wellness subsidies.
    • Relocation and settling-in services.
    • Financial and career planning support.
  • Team composition: 900+ employees from 30+ nationalities; 50% female leaders.
  • Interview process: For science, product, and engineering roles: intro conversation → 2-5 technical exercises → 1-3 interviews (hiring manager + teammates) → values conversation → reference checks.

Application questions