Applied AI Engineer, Australia

The Role

As a Applied AI Engineer on the Applied AI team, you will bridge the gap between Mistral’s cutting-edge AI research and real-world enterprise applications. This role exists to ensure our solutions are robust, scalable, and aligned with both customer needs and Mistral’s technological vision.

The Applied AI team is Mistral’s customer-facing technical organization, working directly with enterprise clients from pre-sales through implementation. We combine deep machine learning expertise with strong customer engagement, operating like startup CTOs who own end-to-end project execution.

By joining this team, you will drive the adoption of Mistral’s products, helping customers deploy AI solutions that deliver measurable business impact across industries.

What You Will Do

• Deploy production-ready AI use cases with significant business impact across diverse industries.

• Develop state-of-the-art GenAI applications, from consumer products to industrial solutions, driving technological transformation for customers.

• Collaborate with researchers, AI engineers, and product teams on complex customer projects involving fine-tuning, advanced LLM applications, and contributions to open-source codebases.

• Participate in pre-sales calls to understand client needs, challenges, and aspirations, providing technical guidance on Mistral’s products.

• Work with product and science teams to continuously improve model and product capabilities based on customer feedback.

• Fluency in English.

• Experience as a technical individual contributor (data scientist or software engineer) on AI-based products.

• Proven track record in implementing AI or machine learning products with APIs, back-end, and front-end interfaces.

• Hands-on experience with fine-tuning LLMs, advanced RAG, or agentic use cases.

• Deep understanding of machine learning and LLM concepts and algorithms.

• Strong technical coding skills in Python.

• Ability to explain complex technical concepts clearly to both technical and non-technical audiences.

• Contributions to open-source projects, particularly in the LLM space.