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Machine Learning Engineer, Open-Source Software - Paris/London

Mistral

Paris Hybrid permanent

Posted: October 4, 2024

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Job Description

About Mistral

At Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life.

We democratize AI through high-performance, optimized, open-source and cutting-edge models, products and solutions. Our comprehensive AI platform is designed to meet enterprise needs, whether on-premises or in cloud environments. Our offerings include le Chat, the AI assistant for life and work.

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 France, USA, UK, Germany and Singapore. We are creative, low-ego and team-spirited.

Join us to be part of a pioneering company shaping the future of AI. Together, we can make a meaningful impact. See more about our culture on https://mistral.ai/careers.

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 and improve Mistral's open-source ecosystem.

About the Open Source Software team

Our OSS team is embedded in our Science team and works very closely with various engineering and marketing teams. All OSS team members can fluidly move on the production / research spectrum depending on where the needs are or where their interests lie

What you will do

• 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, mistral-inference)
• Create and maintain tooling and services: both internal facing (internal research) and external facing (open-source libraries)
• Implement and optimize open-source and internal libraries for performance and accuracy, ensuring production readiness and employing cutting-edge technology and innovative approaches
• Collaborate with the open-source community (PyTorch, vLLM, Hugging Face)

About you

• 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, Transformers, Llama.cpp, ...
• Passion for contributing to the open-source software ecosystem
• Expert programming skills in Python, PyTorch, MLOps
• 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, especially LLMs 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)
• Experience working with Slurm
• Worked with research teams before
• Experience as a core-maintainer of a popular ML open-source library


Location & Remote

This role is primarily based at one of our European offices (Paris, France and London, UK). We will prioritize candidates who either reside there or are open to relocating. We strongly believe in the value of in-person collaboration to foster strong relationships and seamless communication within our team.

In certain specific situations, we will also consider remote candidates based in one of the countries listed in this job posting — currently France & UK. In that case, we ask all new hires to visit our local office:
• for the first week of their onboarding (accommodation and travelling covered)
• then at least 3 days per month

What we offer

💰 Competitive salary and equity
🧑‍⚕️ Health insurance
🚴 Transportation allowance
🥎 Sport allowance
🥕 Meal vouchers
💰 Private pension plan
🍼 Parental : Generous parental leave policy
🌎 Visa sponsorship

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