Research Engineer - Cybersecurity (RL Environments)

Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. As a Research Engineer on the Cybersecurity track, you will push the models' capabilities in vulnerability discovery and remediation, security analysis, incident response, and across the offensive-to-defensive spectrum of cybersecurity. The work sits at the meeting point of research and engineering: devising new approaches and implementing them, including designing and building RL environments that reproduce realistic security scenarios, pipelines that generate synthetic training instances at scale, and experiments and evaluations. Results feed directly into production training runs of frontier models, in close collaboration with Mistral's researchers, engineers, and security specialists.

Responsibilities

Design and implement RL environments simulating cybersecurity scenarios; Build the pipelines and infrastructure that generate synthetic cybersecurity training instances at scale; 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

Requirements

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 have

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

Benefits

Comprehensive benefits package designed to support well-being, growth, and work-life balance, which may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks