Staff Machine Learning Engineer, London, England, United Kingdom

Staff Machine Learning Engineer

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This range is provided by numi. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

Staff Machine Learning Engineer – London (Hybrid) – £115k + Bonus

Ready to lead the next generation of production-grade AI systems?

numi are on the lookout for a Staff Machine Learning Engineer to join a rapidly scaling ML team. You’ll play a key role in building intelligent, scalable systems that power real-time optimisation and personalised user experiences—leveraging cutting-edge ML infrastructure to drive real impact.

From LLM-based personalisation to robust deployment pipelines, this is a high-impact, hands-on role at the intersection of engineering, data science, and product. You’ll define the technical foundations and shape the standards for safe, scalable AI adoption across the organisation.

You’ll be...

Leading the design and implementation of end-to-end ML systems that support both real-time and batch inference.
Building robust pipelines for training, deployment, and monitoring with modern MLOps tooling
Developing resilient services and reusable frameworks to streamline AI product delivery.
Defining and evolving the company’s MLOps strategy—including deployment infrastructure, observability, and governance.
Partnering with data scientists to bring models from prototype to production with clean, scalable interfaces.
Driving architectural reviews, mentoring engineers, and setting engineering best practices for ML systems.

About you...

5+ years of experience building and scaling ML systems in production environments.
Strong Python skills and deep familiarity with modern ML and MLOps tools (e.g. Kubeflow, Airflow, Vertex AI).
Experience with infrastructure-as-code and CI/CD workflows (Terraform, GitHub Actions, ArgoCD, etc.).
Passion for building reliable, scalable infrastructure that powers real-world AI applications.
Strong understanding of the full ML lifecycle—testing, monitoring, versioning, and governance.
Experience leading technical initiatives and mentoring other engineers is a big plus.

Interested? Apply now and help shape the future of scalable AI.

Seniority level

Seniority level
Director

Employment type

Employment type
Full-time

Job function

Industries
Technology, Information and Media

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