Mistral AIApplied AI, Forward Deployed Machine Learning Engineer - London
Mistral AI is hiring an Applied AI, Forward Deployed Machine Learning Engineer - London (United Kingdom). Level rates it ; you can apply on Level.
AI in this role
About Mistral
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.
About The Job
Mistral AI is seeking a Applied AI Engineer to facilitate the adoption of its products among customers and collaborate with them to address complex technical challenges.
The Applied AI team is Mistral's customer-facing technical organization. We work directly with enterprise clients from pre-sales through implementation to deploy cutting-edge AI solutions that deliver measurable business impact.
Our team combines deep ML expertise with strong customer engagement skills, operating like startup CTOs who own end-to-end project execution. By joining the team you'll will bridge the gap between cutting-edge AI research and real-world enterprise applications, ensuring our solutions are robust, scalable, and aligned with both customer needs and Mistral's technological vision.
What you will do
- You’ll individually help deploy into production use cases with a considerable business impact across various industries.
- You’ll work on state-of-the-art GenAI applications from consumer products to industrial use cases, driving with our customers a crucial technological transformation.
- You’ll work in collaboration with our researchers, other AI engineers, product engineers on our most complex customer projects involving complex fine-tuning, state-of-the-art LLM applications, and contributing to our open-source codebases our open source codebases for tasks such as inference and fine-tuning.
- You’ll be involved in pre-sales calls to understand potential clients' needs, challenges, and aspirations. You will provide technical guidance on our products and explain Mistral technologies to various stakeholders.
- Your collaboration with our product and science team to improve continuously our product and model capabilities based on customers’ feedback
How We Work in Applied AI
- We care about people and outputs.
- What matters is what you ship, not the time you spend on it
- Bureaucracy is where urgency goes to vanish. You talk to whoever you need to talk to. The best idea wins, whether it comes from a principal engineer or someone in their first week.
- Always ask why. The best solutions come from deep understanding, not from copying what worked before
- We say what we mean. Feedback is direct, timely, and given because we care.
- No politics. Low ego, high standards.
- We embrace an unstructured environment and find joy in it.
About you
- You are fluent in English
- You have 2+ years as a technical individual contributor (data scientist or software engineer) on AI-based products
- You have proven experience in AI or machine learning product implementation with APIs, back-end and front-end interfaces.
- You have experience in Fine Tuning LLMs, tackling advanced RAG or agentic use cases
- You have deep understanding of concepts and algorithms underlying machine learning and LLMs
- You have strong technical coding skills in Python
- You hold strong communication skills with an ability to explain complex technical concepts in simple terms with technical and non-technical audiences
Ideally you have:
- Contributed to open-source projects in particular in the space of LLMs
- Experience as a Customer Engineer, Forward Deployed Engineer, Sales Engineer, Solutions Architect or Technical Product Manager
- You have experience with deep learning with Pytorch
Why join us?
You’ll have the opportunity to shape the future of AI adoption in enterprises, work with a world-class team, and contribute to open-source projects that impact millions. If you’re excited about leading technical innovation and solving real-world challenges with AI, we’d love to hear from you!
What We Offer
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.
Privacy Policy
Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy.
How we rate this
Applied AI, Forward Deployed Machine Learning Engineer - London at Mistral AI rates 89 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- How would you design a retrieval step so the model answers from real data instead of guessing?
- Walk me through fine-tuning a model: what data did you use, and how did you check the result?
- Tell me about a research question you investigated. What did you find?
- What's a project where you used PyTorch hands-on?
- How would you decide a model or AI system is ready to ship?
Adapt your resume
- List these exact terms on your resume: RAG, Fine-tuning, AI Research, and PyTorch. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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