Senior Machine Learning Engineer (Inference)

The AI industry has a dirty secret.

Behind every intelligent application is a mountain of manual effort. Today, many engineering teams are buried in operational tasks, managing complex infrastructure, and constantly tuning systems just to maintain performance and control costs. It’s slow, expensive, and increasingly unsustainable.

This company is building a different approach...

They’re a growing technology business with strong backing, focused on solving some of the biggest infrastructure challenges facing modern AI systems. Their platform helps organisations improve the performance, efficiency, and scalability of complex ML workloads, tackling problems that become increasingly important as AI adoption grows.

This isn’t a maintenance role, it’s deeply R&D focused. You’ll take ownership of greenfield problems around scaling modern AI systems, improving performance, efficiency, and reliability across complex distributed environments. The work touches everything from model performance to cost optimisation at scale.

You’ll be working at the intersection of machine learning and high performance systems, using a modern stack built around Python and leading ML frameworks, alongside high throughput data systems and cloud-native tooling. You’ll work with modern cloud infrastructure and container orchestration technologies to support demanding AI workloads.

They’re looking for engineers who have spent time in the trenches of ML or data systems, particularly those who have worked on improving inference performance, whether through optimisation, resource efficiency, or system level tuning.

If you’re interested in solving hard scaling problems in a high autonomy environment, it’s worth a conversation.