Mistral AI is seeking an Applied AI Engineer to facilitate the adoption of its products among customers and collaborate with them to address complex technical challenges.
The Applied AI Engineer will be an integral part of our Applied AI Engineering team, which is dedicated to driving the successful deployment of Mistral AI products. They will work hand-in-hand with customers from the pre-sale stage to post-implementation, ensuring our solutions meet and exceed client expectations.
In this role, you’ll manage daily customer relations involving multiple stakeholders (CEO/CTO, data scientists, and software engineers) and function as a key resource in externalising our research in production settings.
Key Responsibilities:
- You’ll be responsible for onboarding customers on our products and APIs, providing guidance on prompting, evaluation, and fine-tuning, and ensuring the best production integration with back-end and front-end interfaces.
- 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 individually help deploy into production use cases with a considerable business impact across various industries.
- You’ll work in collaboration with our researchers, other AI engineers, and product engineers on our most complex customer projects involving complex fine-tuning, state-of-the-art LLM applications, and contributing to our open-source codebase 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.
Required Skills & Qualifications:
Must haves:
- PhD / master in AI / data science.
- 2+ years as a technical individual contributor (machine learning engineer or data scientist or software engineer) on AI-based products.
- Experience in Fine Tuning LLMs, tackling advanced RAG or agentic use cases.
- Experience in MLOps and deploying Machine Learning use cases at scale.
- Deep understanding of concepts and algorithms underlying machine learning and LLMs.
- Experience building and deploying LLMs or NLP applications.
- Proven experience in AI or machine learning product implementation with APIs, back-end and front-end interfaces.
- Strong technical coding skills in Python.
- Experience in deep learning with Pytorch.
- Experience with Agents framework such as Langchain, vector DBs.
- Strong communication skills with an ability to explain complex technical concepts in simple terms to technical and non-technical audiences.
Nice to Haves:
- Experience as a Customer Engineer, Forward Deployed Engineer, Sales Engineer, Solutions Architect, or Technical Product Manager.
- You have contributed to open-source projects, particularly in the space of LLMs.
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