Mistral5mo ago
Applied AI, Forward Deployed Machine Learning Engineer - Morocco
Casablanca · CasablancaFull-timemid
Data ScienceMachine Learning EngineerDataMachine LearningData & AI
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Quick Summary
Overview
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.
Technical Tools
Data ScienceMachine Learning EngineerDataMachine LearningData & AI
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
Listing Details
- Posted
- November 4, 2025
- First seen
- March 25, 2026
- Last seen
- April 24, 2026
Posting Health
- Days active
- 29
- Repost count
- 0
- Trust Level
- 23%
- Scored at
- April 24, 2026
Signal breakdown
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External application · ~5 min on Mistral's site
Please let Mistral know you found this job on Jobera.
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