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Mistral AI
NewDesign and build reinforcement learning environments that simulate realistic cybersecurity scenarios for training AI models in vulnerability discovery, security analysis, and incident response. You'll create synthetic training pipelines at scale, run experiments evaluating model capabilities, and manage infrastructure including containers, sandboxes, and Kubernetes deployments. The role requires hands-on cybersecurity expertise (offensive or defensive), strong Python skills, DevOps experience, and comfort collaborating across research and engineering teams. Based remotely across distributed offices.
Written from this posting by Neural Jobs AI. The full description is below.
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.
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.
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.
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.
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.
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.
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Mistral AI develops open-weight and commercial large language models, along with Le Chat and a developer platform for building on them.
Founded in Paris in 2023 by researchers from DeepMind and Meta, it is Europe's most prominent frontier-model lab.
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