London | Remote

You’ll take ownership of the product that helps businesses build, train and deploy machine learning models at scale.

This is an opportunity to lead product direction within a growing AI infrastructure business. You’ll define the longer-term vision, decide what gets built and work closely with engineers, ML specialists and customers to improve how AI models are developed and operated.

The product covers some of the biggest challenges in machine learning infrastructure: how models are trained and fine-tuned, how GPU resources are used, and how models are deployed and served efficiently in production.

You’ll have genuine product ownership. Rather than simply managing a delivery backlog, you’ll shape the roadmap, identify opportunities to improve the platform and turn complex technical and customer requirements into clear product decisions.

You’ll also work closely with engineering and customers, gaining direct insight into how organisations are building and deploying AI and using that feedback to influence the future direction of the platform.

This could suit you if you’re already a Technical Product Manager working on ML platforms, cloud infrastructure, MLOps or developer tooling and want to take ownership of a product in a fast-moving AI market.

You’ll need:

  • 5+ years of Product Management experience, ideally owning technical platform or infrastructure products
  • Experience with ML platforms, MLOps, AI infrastructure or cloud-based developer products
  • A good understanding of machine learning workflows, including model training, deployment and inference
  • Knowledge of technologies such as Kubernetes, PyTorch, Ray, Slurm or similar
  • Experience defining product strategy, building longer-term roadmaps and working closely with engineering teams and technical customers
  • A strong technical understanding through education or hands-on experience

Experience with GPU infrastructure, distributed computing or model serving would be particularly relevant.

London | Remote

If you’re interested in owning a product at the intersection of AI, machine learning and infrastructure, I’d be happy to tell you more.