EU remote
Research Engineer, Forge
About this role
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. Role summary As a Research Engineer on Forge, you will turn real customer requirements into reliable training and deployment workflows. You’ll work end‑to‑end across model adaptation and post‑training (CPT/SFT/RL/distillation), evaluation, data, and infrastructure.
The role bridges research experimentation and production constraints. This role sits in Applied Science, with direct impact on client outcomes. You’ll collaborate closely with scientists, engineers, product, and customer‑facing teams to ensure Forge projects ship, are maintainable, and can be trusted by others. Interview focus can vary (algorithms, infrastructure, evals, or data). You don’t need to match every bullet below to apply.
What you will do Build and improve post‑training and evaluation workflows (CPT/SFT/RL/distillation), turning prototypes into repeatable Forge “recipes”. Develop tools and pipelines for synthetic data generation, data curation, training, evaluation, and deployment. Debug and harden large‑scale ML systems: distributed training, scheduling/execution, checkpointing, observability, and reproducibility. Improve the Forge codebase via clear APIs, tests, documentation, and maintainable abstractions.
Push the frontier of our RL training stack (e.g., high-throughput async rollout and scalable post‑training systems at frontier-model scale) Make sure Forge deployment is seamless and adaptable to a diversity of clients (hardware access, software stack, cloud and on-premises, …) Partner with researchers and infrastructure engineers to translate bottlenecks into concrete system improvements. About you Strong Python engineering skills and experience working in large codebases (testing, code review, CI, operational ownership).