
Leading company in the artificial intelligence industry
Machine Learning Engineer, Open-Source Software - Paris/London
必备技能
Python
PyTorch
Machine Learning
MLOps
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 (Py Torch, 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 Py Torch, Tensorflow, JAX, vLLM, Transformers, Llama.cpp, ...
- Passion for contributing to the open-source software ecosystem
- Expert programming skills in Python, Py Torch, 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
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关于Mistral AI

Mistral AI
Series BMistral AI SAS is a French artificial intelligence (AI) company, headquartered in Paris. Founded in 2023, it has open-weight large language models (LLMs), with both open-source and proprietary AI models. As of 2025 the company has a valuation of more than US$14 billion.
51-200
员工数
Paris
总部位置
$6.0B
企业估值
评价
10条评价
3.8
10条评价
工作生活平衡
2.8
薪酬
4.0
企业文化
4.2
职业发展
3.5
管理层
2.5
72%
推荐率
优点
Supportive team and collaborative environment
Good learning opportunities and mentorship programs
Excellent benefits and competitive compensation
缺点
Poor management and lack of leadership direction
Work-life balance issues and heavy workload
High stress environment and burnout
薪资范围
36个数据点
Mid/L4
Senior/L5
Staff/L6
Mid/L4 · AI SCIENTIST
8份报告
$300,000
年薪总额
基本工资
$300,000
股票
-
奖金
-
$390,000
$429,000
面试评价
1条评价
难度
3.0
/ 5
时长
21-35周
面试流程
1
Application Review
2
Recruiter Screen
3
Technical Interview
4
Research Discussion
5
Team Matching
6
Offer
常见问题
Machine Learning/AI Concepts
Research Experience
Technical Knowledge
Coding/Algorithm
Behavioral/STAR
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