AI Engineer

What You Can Expect

We're looking for an AI Engineer to join our Connected Health team at Zimmer Biomet. This is a fully remote, UK-based job. You'll design, build, deploy and improve generative AI and data-driven products that raise the quality of care and quality of life for orthopaedic patients worldwide.

You'll join our AI & Data Science team, which works across three areas:

• Product development: We develop prediction and decision-support algorithms, using classical ML and generative AI, for our patient- and clinician-facing applications.
• Product analysis: We help our product teams understand how people use our products, so they can make better decisions.
• Platform development: We build tooling and reusable infrastructure that supports AI and data-driven product development across Zimmer Biomet. We design it to follow best practice for Software as a Medical Device (SaMD).

We aim to keep improving, to communicate openly, and to enjoy ourselves along the way.

How You'll Create Impact

In this role you will work closely with machine learning scientists and application software engineers to bring advanced data insights to life. You'll build automation pipelines, deploy and serve both predictive models and generative AI systems, integrate third-party platforms and tooling, and design for observability and monitoring in production, whilst ensuring that we meet our regulatory commitments.

Our work covers classical ML on structured, sensor and imaging data, and generative AI: retrieval-augmented generation and agentic systems. Because we build medical devices in a regulated context, quality, traceability and responsible AI matter at every step. You'll help us productionise these systems against standards including the EU AI Act and FDA guidance on AI/ML-enabled medical devices.

You'll help shape our technical roadmap and influence how the Connected Health team moves forward with AI products.

Today, our tooling revolves around:

• Azure ML and Azure DevOps for model orchestration, CI/CD and development;
• Python for data pipelines, machine learning pipelines and model serving;
• MLflow (or similar) for experiment tracking and model registry, with monitoring for drift and performance in production;
• LLM/GenAI tooling including foundation-model APIs, vector stores/retrieval, orchestration frameworks and evaluation harnesses;
• Pulumi for infrastructure as code;
• Occasionally C# to support integration between our internal systems.

We also use modern developer tooling. Responsible use of AI coding assistants like Claude Code is part of how we work day-to-day.

What Makes You Stand Out

• A passion for building generative AI and data-driven products to improve healthcare;
• The idea of shaping AI products excites you, and you’re comfortable working where requirements are still evolving;
• Your background covers the majority of the end-to-end lifecycle of a AI/ML product, from containerisation, CI/CD, infrastructure deployment to debugging and monitoring models in production;
• Hands-on experience with either classical ML or generative AI in production, and have a genuine interest in the other;
• The ability to build cloud-native applications and are comfortable with infrastructure as code;
• You can communicate analyses and technical ideas, and their value, to a range of audiences;
• A drive to learn about new technologies and methodologies;

If you don't meet every requirement but are excited by this role, we'd still like to hear from you!

Your Background

• A demonstrable background within healthcare data and/or delivering AI/ML in regulated spaces (SaMD, EU AI Act, FDA);
• Prior knowledge of evaluating and guard-railing generative AI systems
• Experience with model monitoring, drift detection and responsible-AI practices (fairness, robustness, explainability).
• Industry experience as a Machine Learning, AI or Data Engineer;
• Comfortable programming with Python and packages associated with the AI/ML workflow;

Travel & Logistic Expectations