Mistral AI
Machine Learning Engineer – Open-Source Software (Paris/London)
Job Description
Role Summary – You will be in charge of open-sourcing state-of-the-art models, whilst maintaining and improving Mistral’s publicly available libraries. Your work is critical in helping turn research breakthroughs into tangible solutions- Location: Paris / London
Key Responsibilities – Releasing our models to open source platforms and libraries, e.g. vLLM, GitHub, Hugging Face- Maintaining Mistral’s open source libraries (mistral-common, mistral-finetune, mistralai)- Create and maintain tooling and services: both internal facing (internal research) and external facing (open-source libraries)- Implement and optimize open-source libraries for performance and accuracy, ensuring production readiness and employing cutting-edge technology and innovative approaches- Collaborate with the open-source community and scout for novel inference & training frameworks as well as research 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 & profile – Master’s degree in Computer Science, Machine Learning, Data Science, or a related field- Experience contributing to popular open-source libraries such as PyTorch, Tensorflow, JAX, vLLM, … – Passion for contributing to the open-source software ecosystem – Expert programming skills in Python, MLOps – Proficiency in frameworks like PyTorch, Jax 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
Now, it would be ideal if you have;- Experience with training and fine-tuning large language models (e.g., distillation, supervised fine-tuning, policy optimization)- Worked with LLMs- Worked with research teams before- Experience as a core-maintainer of a popular ML open-source library
About Mistral – At Mistral AI, our mission is to make AI ubiquitous and open. We are passionate about bridging the gap between technology and businesses of all sizes.- We are a leading innovator in the field of open-source large language models. Our advanced LLM solutions can be seamlessly deployed on any cloud, allowing for optimized integration and robust performance. Developers are using our API via la Plateforme to build incredible AI-first applications powered by our models that can understand and generate natural language text and code.- We are multilingual at our core. We released le Chat, as a demonstrator of our models.- We are a tight-knit, nimble team dedicated to bringing our cutting-edge AI technology to the world. Our teams are distributed between France, UK and USA- 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.
Key Responsibilities – Releasing our models to open source platforms and libraries, e.g. vLLM, GitHub, Hugging Face- Maintaining Mistral’s open source libraries (mistral-common, mistral-finetune, mistralai)- Create and maintain tooling and services: both internal facing (internal research) and external facing (open-source libraries)- Implement and optimize open-source libraries for performance and accuracy, ensuring production readiness and employing cutting-edge technology and innovative approaches- Collaborate with the open-source community and scout for novel inference & training frameworks as well as research 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 & profile – Master’s degree in Computer Science, Machine Learning, Data Science, or a related field- Experience contributing to popular open-source libraries such as PyTorch, Tensorflow, JAX, vLLM, … – Passion for contributing to the open-source software ecosystem – Expert programming skills in Python, MLOps – Proficiency in frameworks like PyTorch, Jax 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
Now, it would be ideal if you have;- Experience with training and fine-tuning large language models (e.g., distillation, supervised fine-tuning, policy optimization)- Worked with LLMs- Worked with research teams before- Experience as a core-maintainer of a popular ML open-source library
About Mistral – At Mistral AI, our mission is to make AI ubiquitous and open. We are passionate about bridging the gap between technology and businesses of all sizes.- We are a leading innovator in the field of open-source large language models. Our advanced LLM solutions can be seamlessly deployed on any cloud, allowing for optimized integration and robust performance. Developers are using our API via la Plateforme to build incredible AI-first applications powered by our models that can understand and generate natural language text and code.- We are multilingual at our core. We released le Chat, as a demonstrator of our models.- We are a tight-knit, nimble team dedicated to bringing our cutting-edge AI technology to the world. Our teams are distributed between France, UK and USA- 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.
