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Mistral AI

Research Engineer – Cybersecurity, RL Environments

Mistral AI

. Design and implement RL environments simulating cybersecurity scenarios .

Posted 9/25/2026full-timeParis • FranceMid-LevelSeniorWebsite

Tech Stack

Tools & technologies
CloudCyber SecurityDockerKubernetesPythonC++

About the role

Key responsibilities & impact
  • Design and implement RL environments simulating cybersecurity scenarios
  • Build pipelines and infrastructure generating synthetic cybersecurity training instances at scale
  • Conduct experiments and evaluations of model capabilities, from quick prototypes to controlled benchmark runs
  • Own infrastructure including containers, sandboxes, VMs, cloud deployments, and Kubernetes orchestration, managed as code
  • Partner with researchers and security specialists to turn domain expertise into reproducible environments and datasets
  • Write clear, efficient Python code and enforce testing, code review, and CI/CD practices
  • Develop model capabilities in vulnerability discovery and remediation, security analysis, and incident response across offensive and defensive cybersecurity
  • Feed results into production training runs for frontier models

Requirements

What you’ll need
  • Hands-on expertise in offensive and/or defensive cybersecurity, including vulnerability analysis, web/network/cloud security, secure coding practices, and SOC
  • Strong software engineering skills with clean, reliable, well-tested code
  • Fluency in Python
  • Comfort reading lower-level languages such as C/C++ for vulnerability analysis
  • DevOps experience with Docker, Kubernetes, cloud deployments, and sandboxed or simulated environments
  • Working knowledge of RL techniques and LLM training methodologies, or strong motivation to develop it
  • Self-starter, low-ego, collaborative, and comfortable working across research and engineering
  • CTF, cyber-range, or bug-bounty experience is a nice-to-have
  • Research background in cybersecurity or another experimental discipline is a nice-to-have
  • Prior experience building RL environments or large-scale ML training infrastructure is a nice-to-have
  • Relevant open-source contributions and projects are a nice-to-have

Benefits

Comp & perks
  • Healthcare coverage
  • Parental leave
  • Retirement plans
  • Relocation support
  • Wellness programs
  • Meal allowances
  • Transportation allowances
  • Other location-specific perks