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ML Platform Engineer Jobs

Engineers who build and maintain the infrastructure that powers machine learning workflows. A critical role in scaling ML operations from prototype to production.

Open roles
24
Salary range
£53k – £108k
Hiring companies
15
View 24 live roles → Get an alert

ML Platform Engineers are the backbone of any organisation that relies heavily on machine learning. They design, build, and maintain the infrastructure that supports the entire ML lifecycle, from data ingestion and model training to deployment and monitoring. These engineers work closely with data scientists, ML researchers, and DevOps teams to ensure that ML models can be efficiently and reliably deployed at scale. Whether in a research-heavy startup or a large enterprise, the role is crucial for turning theoretical models into practical, production-ready solutions.

What the role does

Inside the role of an ML Platform Engineer

A typical week is split between developing and maintaining infrastructure, collaborating with cross-functional teams, and ensuring the smooth operation of ML workflows.

  1. 01
    Design and implement scalable ML infrastructure.
  2. 02
    Collaborate with data scientists to optimise model training pipelines.
  3. 03
    Monitor and troubleshoot production ML systems.
  4. 04
    Integrate new tools and technologies into the ML platform.
  5. 05
    Document and maintain system architecture and processes.
  6. 06
    Participate in code reviews and contribute to team knowledge sharing.
Salary on the board

£53k – £108k

Based on advertised midpoints across the 13 UK listings priced in pounds in the last 12 months. Base salary only.

Salary visibility
16% of listings advertise a salary.
By seniority
£k base
Senior
50
130
6 jobs
Skills & tools

What hiring managers ask for

% of 21 listings posted in the last 12 months that mention each skill, extracted from job descriptions.

Python
71%
Terraform
71%
Kubernetes
67%
CI/CD
52%
AWS
43%
Go
29%
Azure
29%
GCP
29%
Docker
24%
GitHub Actions
24%
Distributed Systems
24%
Grafana
19%
Career ladder

From Junior to Principal

A typical UK progression for ml platform engineers. Years are guidance — strong people move faster, and many senior folks sidestep into research, product or management.

  1. Level 1

    Junior ML Platform Engineer

    0–2 yrs

    Assists in the development and maintenance of ML infrastructure, focusing on learning and contributing to smaller projects.

  2. Level 2

    ML Platform Engineer

    2–5 yrs

    Takes ownership of specific components of the ML platform, ensuring they are scalable, reliable, and efficient.

  3. Level 3

    Senior ML Platform Engineer

    5–8 yrs

    Leads the design and implementation of complex ML infrastructure, guiding junior engineers and driving innovation.

  4. Level 4

    Principal ML Platform Engineer

    8+ yrs

    Strategises and oversees the entire ML platform, influencing organisational direction and leading major initiatives.

Pathway

How to become a ML Platform Engineer

There's no single route, but most people follow some version of these steps.

  1. 1

    Learn the Basics

    Gain foundational knowledge in ML, DevOps, and cloud computing. Start with small projects to understand the ML workflow.

  2. 2

    Build Practical Skills

    Work on real-world projects, focusing on developing and maintaining ML infrastructure. Collaborate with data scientists and DevOps teams.

  3. 3

    Specialise in ML Platforms

    Deepen your expertise in ML platform engineering, including advanced topics like MLOps and model deployment.

  4. 4

    Lead Projects

    Take on leadership roles, overseeing the design and implementation of large-scale ML infrastructure projects.

  5. 5

    Influence Strategy

    Contribute to the strategic direction of the organisation, driving innovation and efficiency in ML operations.

  6. 6

    Mentor and Innovate

    Mentor junior engineers, foster a culture of continuous learning, and lead cutting-edge research and development in ML platforms.

Live jobs

24 live roles

See all 24 roles →
Wayve logo

Senior Software Engineer - Runtime Platform, Robot Software

This role involves developing and optimizing the software stack for Wayve's autonomous driving vehicles, focusing on performance, latency, and system efficiency. You will work closely with multiple teams to identify and resolve bottlenecks, implement profiling tools, and enhance the overall system performance.

Wayve London, United Kingdom

Forward Deployed Engineer, Agentic Platform (UK Public Sector)

Design, build, and deploy production-grade LLM-powered agentic workflows for enterprise clients in high-regulation sectors. Translate ambiguous business problems into secure, reliable AI agents integrated with tools, APIs, and sensitive data sources. Contribute to North, Cohere’s AI workspace platform, across the full product lifecycle while shaping cross-customer frameworks and ensuring auditability, safety, and performance.

Cohere United Kingdom
Remote Permanent

Staff Software Engineer, Kubernetes Platform

This role involves owning and scaling the Kubernetes control plane for large AI training clusters, including customizing the scheduler for topology-aware ML workloads and ensuring high availability under extreme scale. The engineer will build core platform services like service discovery, develop controllers and operators, and collaborate closely with research and infrastructure teams. The position demands deep expertise in distributed systems, Kubernetes internals, and debugging complex production issues across cloud environments.

Anthropic London, United Kingdom £325,000 – £485,000 pa
On-site Permanent

Forward Deployed Engineer, Agentic Platform (Europe)

This role involves working closely with enterprise customers to design, build, and deploy AI-powered agents that solve complex business problems. You will lead the development of agentic workflows using LLMs, ensuring reliability, security, and performance, while also contributing to the North AI workspace platform.

Cohere London, United Kingdom
Hybrid Permanent
Wayve logo

Engineering Manager, Runtime Platform, Robot Software

Lead and grow a new engineering team building the runtime foundations for an AI-driven vehicle system, including real-time middleware, performance optimization, and observability. Guide technical direction for low-latency embedded software while fostering team development and cross-team collaboration. The role is central to enabling scalable, high-performance AI deployment across diverse vehicle platforms.

Wayve London, United Kingdom

Senior Golang Engineer - AI Products & Platforms - Citi

This role involves designing and building AI-powered products and platforms using Golang within Citi's Chief Technology Office. You'll develop high-performance, cloud-native backend services and APIs at enterprise scale, working closely with AI and product teams to deliver production-ready solutions. The position emphasizes solving complex distributed systems challenges while mentoring engineers and advancing engineering best practices in a lean, collaborative environment.

eFinancialCareers London, United Kingdom
Hybrid Permanent
Wayve logo

Staff Software Engineer, Data Enrichment Platform

This role involves owning the technical vision for a data enrichment platform that processes petabytes of driving data, supports large GPU fleets, and enables model engineers. Responsibilities include leading backend development, building scalable systems, and partnering with cross-functional teams to improve model quality and reduce operational costs.

Wayve London, United Kingdom
Wayve logo

Full-Stack Software Engineer, Model Development Platform

Design and build full-stack applications that streamline model development workflows for autonomous driving systems, including experiment scheduling, evaluation, and on-road testing. Collaborate closely with researchers and engineers to deliver scalable, secure backend services and intuitive web interfaces. Take technical ownership from concept to production, with a focus on reliability, observability, and system integration.

Wayve United Kingdom
See all 24 roles →
Top hirers

Companies hiring ml platform engineers

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Hiring locations

Where this role is hiring

The locations with the most live listings for this role today.

London

Location
19 open

Cambridge

Location
1 open
FAQs

Common questions

  • Essential skills include proficiency in programming languages like Python and Java, knowledge of cloud platforms (AWS, GCP, Azure), and experience with DevOps tools and practices.

  • ML Platform Engineers collaborate closely with data scientists to understand their needs, optimise model training pipelines, and ensure that models can be deployed and scaled effectively.

  • Key challenges include managing the complexity of ML workflows, ensuring high availability and performance of ML systems, and keeping up with rapidly evolving technologies and best practices.

  • Career progression typically involves moving from hands-on technical roles to leadership positions, where you can influence the strategic direction of ML operations and mentor junior engineers.

  • Salary ranges can vary widely based on experience, location, and company size. For more detailed information, please refer to the salary section on this page.

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