Mistral AI에서 대규모 머신러닝 파이프라인을 구축하고 최적화할 Research Engineer를 채용합니다. Python 및 PyTorch/JAX 활용 능력과 분산 학습(Distributed Training) 경험이 필수입니다. 연구와 프로덕션 환경을 잇는 핵심 역할을 수행하며, LLM 및 딥러닝 분야의 전문성을 발휘할 수 있습니다. 글로벌 팀과 협업하며 최첨단 AI 모델을 개발할 기회입니다.
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 team spans Platform (shared infra & clean code) and Embedded (inside research squads). Engineers can move along the research↔production spectrum as needs or interests evolve.
As a Research Engineer – ML track, you’ll build and optimise the large-scale learning systems that power our open-weight models. Working hand-in-hand with Research Scientists, you’ll either join:
Platform RE Team: Enhance the shared training framework, data pipelines and cluster tooling used by every team; or
Embedded RE Team: Sit inside a research squad (Alignment, Pre-training, Multimodal, Safety …) and turn fresh ideas into repeatable, scalable code.
Accelerate researchers by taking on the heavy parts of large-scale ML pipelines and building robust tools.
Interface cutting-edge research with production: integrate checkpoints, streamline evaluation, and expose APIs.
Conduct experiments on the latest deep-learning techniques (sparsified 70 B + runs, distributed training on thousands of GPUs).
Design, implement and benchmark ML algorithms; write clear, efficient code in Python.
Deliver prototypes that become production-grade components for Le Chat and our enterprise API.
Master’s or PhD in Computer Science (or equivalent proven track record).
4 + years working on large-scale ML codebases.
Hands-on with PyTorch, JAX or TensorFlow; comfortable with distributed training (DeepSpeed / FSDP / SLURM / K8s).
Experience in deep learning, NLP or LLMs; bonus for CUDA or data-pipeline chops.
Strong software-design instincts: testing, code review, CI/CD.
Self-starter, low-ego, collaborative.
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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