Machine Learning Engineer (Paris/London)

About Mistral- At Mistral AI, we are a tight-knit, nimble team dedicated to bringing our cutting-edge AI technology to the world. Our mission is to make AI ubiquitous and open.- We are creative, low-ego, team-spirited, and have been passionate about AI for years.- We hire people who thrive in competitive environments, because they find them more fun to work in. We hire passionate women and men from all over the world.- Our teams are distributed between France, UK and USA.Role Summary- You will be in charge of deploying state-of-the-art models in production environments, helping turn research breakthroughs into tangible solutions.- Location: Paris / London.Key ResponsibilitiesCreate and maintain tooling and services: both internal facing (research & dogfooding) and external facing (product).Collaborate cross-functionally with researchers, software engineers, and product managers to understand complex business challenges and deliver AI-powered solutions.Implement and optimize ML pipelines for performance and accuracy, ensuring production readiness and employing cutting-edge technology and innovative approaches.About the ML Engineering team- Our ML Engineering team is embedded in our Product development organization (SWE & Product) team and works very closely with our Science team.- All our engineers can fluidly move on the production/research spectrum depending on where the needs are or where their interests lie.Qualifications & ProfileMaster's degree in Computer Science, Machine Learning, Data Science, or a related field.Expert programming skills in Python, MLOps or FullStack + ML experience.Proficiency in frameworks like PyTorch or TensorFlow.Adaptable, proactive and autonomous.Attention to detail and a drive to go the last mile to build almost perfect tools.Deep understanding of machine learning approaches and algorithms.Low-ego.Collaborative and have a real team player mindset.Preferred QualificationsExperience with training and fine-tuning large language models (e.g., distillation, supervised fine-tuning, policy optimization).Worked with LLMs.Worked with research teams before. #J-18808-Ljbffr