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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
3
Hiring companies
2
View 3 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.
Skills & tools

What hiring managers ask for

% of 2 listings posted in the last 12 months that mention each skill, extracted from job descriptions.

Python
100%
Kubernetes
100%
Machine Learning
50%
AI
50%
CI/CD
50%
SRE
50%
Docker
50%
Networking
50%
Compute
50%
Storage
50%
Cloud Infrastructure
50%
Distributed Systems
50%
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

3 live roles

Synthesia logo

ML Platform Engineer

This role involves designing and maintaining the ML platform infrastructure that supports model training, evaluation, and production serving at scale. The engineer will build reliable, automated systems for deploying and operating generative models, with a focus on scalability, observability, and developer experience. The position bridges research and production engineering, emphasizing robust tooling and agentic workflows to reduce manual operational overhead.

Synthesia London, United Kingdom
Remote Permanent
Synthesia logo

Principal ML Platform Engineer

Synthesia is the world’s leading AI video platform for business, used by over 90% of the Fortune 100. Founded in 2017, the company is headquartered in London, with offices and teams across Europe and the US.As AI continues to shape...

Synthesia London, United Kingdom
Remote Permanent
Isomorphic Labs logo

Director of Engineering (ML Platform), London

This role involves leading the strategic direction and operational excellence of the Platform teams, which are crucial for training and serving large-scale machine learning models in biotech. You will define the long-term vision, mentor a diverse team, and ensure robust, scalable, and developer-friendly services across multiple disciplines.

Isomorphic Labs London, United Kingdom
On-site Permanent
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
3 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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