# Applied AI, Forward Deployed Machine Learning Engineer

**Company**: Mistral AI
**Location**: Munich
**Work arrangement**: onsite
**Experience**: mid
**Job type**: full-time
**Category**: Engineering
**Industry**: Technology
**Wikidata**: https://www.wikidata.org/wiki/Q119718658

**Apply**: https://jobs.lever.co/mistral/aff9f13c-e79f-4d66-98b1-f62dd1c552cd?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_10a4fc36-366

## Description

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 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

## Skills

### Required
- Python
- Machine Learning
- Deep Learning
- PyTorch
- Fine Tuning LLMs
- APIs
- Back-end and Front-end Interfaces

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Source: [Apply at jobs.lever.co](https://jobs.lever.co/mistral/aff9f13c-e79f-4d66-98b1-f62dd1c552cd?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)
