What you do

• Build ML and AI models: recommendation, prediction and generative use cases
• Set up ML pipelines and take models to production, including training, deployment and retraining
• Put monitoring and observability in place for AI workloads, and watch performance, latency and reliability
• Integrate LLMs and AI APIs into working workflows, copilots and agents
• Translate business use cases into scalable solutions and advise on architecture choices

You work with data engineering, software engineering, product and external AI partners. A large part of your time is spent in direct contact with the business.

What you bring

• 4 to 7 years in ML engineering, AI engineering or platform engineering
• A foundation in machine learning, not only in LLMs. You understand what happens under the hood
• Strong Python and experience with production environments for AI
• Experience with LLMs, AI APIs, vector databases, orchestration frameworks and CI/CD on a cloud platform
• An understanding of data engineering and API architecture
• You can explain technical choices clearly to people without a technical background

You do not need to tick every box. Come close and I would like to hear from you.