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Machine Learning Engineer Jobs

Engineers who build and deploy machine learning models. A core role in the AI ecosystem, combining software engineering with data science.

Open roles
47
Salary range
£45k – £156k
Hiring companies
25
View 47 live roles → Get an alert

Machine Learning Engineers are at the heart of the AI revolution. They design, build, and deploy machine learning models that power everything from recommendation systems to autonomous vehicles. These roles are found in a wide range of organisations, from tech giants and research-heavy startups to scaleups and the larger consultancies. The work is highly technical, requiring a deep understanding of both software engineering and data science principles.

What the role does

Inside the role of a Machine Learning Engineer

A typical week for a Machine Learning Engineer is a mix of coding, model training, and collaboration with data scientists and other engineers.

  1. 01
    Develop and optimise machine learning models.
  2. 02
    Collaborate with data scientists to refine datasets.
  3. 03
    Integrate models into production systems.
  4. 04
    Monitor and maintain model performance.
  5. 05
    Document and present findings to the team.
  6. 06
    Stay updated with the latest research and tools.
Salary on the board

£45k – £156k

Based on advertised midpoints across the 62 priced listings posted in the last 12 months. Base salary only.

Salary visibility
2% of listings advertise a salary — up from 0% the year before.
By seniority
£k base
Mid
45
160
24 jobs
Senior
50
124
13 jobs
Lead
80
168
13 jobs
Skills & tools

What hiring managers ask for

% of 84 listings posted in the last 12 months that mention each skill, extracted from job descriptions.

Python
85%
Machine Learning
61%
PyTorch
49%
TensorFlow
38%
MLOps
36%
AWS
26%
Azure
25%
Kubernetes
24%
CI/CD
23%
Docker
20%
SQL
19%
GCP
19%
Career ladder

From Junior to Principal

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

  1. Level 1

    Junior Machine Learning Engineer

    0–2 yrs

    Assist in the development and testing of machine learning models, with a focus on learning and gaining hands-on experience.

  2. Level 2

    Machine Learning Engineer

    2–5 yrs

    Own the development and deployment of machine learning models, working closely with data scientists and other engineers.

  3. Level 3

    Senior Machine Learning Engineer

    5–8 yrs

    Lead the design and implementation of complex machine learning systems, mentoring junior engineers and driving innovation.

  4. Level 4

    Principal Machine Learning Engineer

    8+ yrs

    Strategise and oversee the AI roadmap, influencing the direction of the organisation's machine learning efforts and leading large teams.

Pathway

How to become a Machine Learning Engineer

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

  1. 1

    Learn the Fundamentals

    Gain a strong foundation in programming, mathematics, and statistics. Familiarise yourself with key machine learning concepts and tools.

  2. 2

    Build Projects

    Apply your knowledge by building machine learning projects. This could be through personal projects, internships, or university coursework.

  3. 3

    Gain Industry Experience

    Start your career as a Junior Machine Learning Engineer, working on real-world problems and learning from experienced colleagues.

  4. 4

    Specialise and Advance

    Develop expertise in specific areas of machine learning, such as natural language processing or computer vision. Progress to more senior roles.

  5. 5

    Lead and Innovate

    Take on leadership roles, driving the development of cutting-edge AI solutions and mentoring the next generation of machine learning engineers.

  6. 6

    Influence Strategy

    Shape the AI strategy of your organisation, influencing key decisions and leading large-scale machine learning initiatives.

Live jobs

47 live roles

See all 47 roles →
Faculty AI logo

Machine Learning Engineer

Develop and deploy production-grade machine learning systems for high-impact clients, particularly in the defence sector. Work across the full ML lifecycle, from scalable architecture design to operationalisation, using cloud platforms and containerisation tools. Collaborate with cross-functional teams to deliver ethical, reliable AI solutions in real-world environments.

Faculty AI London, United Kingdom
Hybrid Permanent Flexible Clearance Required
PhysicsX logo

Machine Learning Engineer

A Machine Learning Engineer will collaborate with simulation engineers, data scientists, and customers to solve complex physics and engineering challenges using AI. The role involves building scalable, reliable ML data pipelines, working with 3D point-cloud and mesh data, and translating R&D into reusable tools and products. Frequent customer site visits across multiple continents are expected to support on-site solution development and deployment.

PhysicsX England US$150,000 – US$190,000 pa
On-site Permanent Clearance Required
ECM Selection logo

Machine Learning Engineer

This role involves developing end-to-end machine learning systems integrated with advanced electronics for defence and security applications. You'll work across diverse domains such as computer vision and generative models, building functional prototypes and demonstrators. The role emphasizes innovation, rapid iteration across projects, and close collaboration in a technically driven, low-management environment.

ECM Selection Cambridge, Cambridgeshire, United Kingdom £40,000 – £70,000 pa
On-site Permanent Clearance Required
PhysicsX logo

Machine Learning Engineer

A Senior Machine Learning Engineer will lead the deployment of AI models into production environments for engineering and physics simulation, working closely with customers and cross-functional teams. The role involves building scalable ML pipelines, mentoring engineers, and translating R&D into practical tools using technologies like PyTorch, Kubeflow, and fastAPI. Frequent international travel is required for on-site collaboration.

PhysicsX United Kingdom
Hybrid Permanent

Machine learning Engineer

This role involves building and deploying production-grade machine learning systems for diverse clients, translating research into real-world applications. You'll work across the full ML lifecycle, design scalable software architectures, and collaborate with cross-functional teams to deliver impactful AI solutions. The position emphasizes technical leadership, cloud infrastructure, and best practices in ML deployment.

Faculty London, United Kingdom
Hybrid Permanent

Machine Learning Engineer

This role involves designing, building, and deploying advanced machine learning models to solve complex operational challenges in real-world environments. You will work closely with a high-calibre founding team, industrial data, and customer environments to take machine learning systems from early validation through to scalable deployment.

Platform Recruitment London, United Kingdom £60,000 – £70,000 pa
On-site Permanent

Machine Learning Engineer

This role involves deploying and managing machine learning models in production using Azure Machine Learning, with a focus on building and maintaining MLOps infrastructure and CI/CD pipelines. The engineer will support real-time inference, data pipelines, and scalable ML workloads while collaborating with data scientists and DevOps teams. Responsibilities include monitoring, security, governance, and technical documentation within an Azure cloud environment.

Queen Square Recruitment Wokingham, Berkshire, United Kingdom £460 pd
Wayve logo

Machine Learning Engineer, ADAS

Train and improve computer vision and 3D perception models for ADAS systems, working across the full ML lifecycle from data to deployment. Build scalable data pipelines, including auto-labelling and 3D reconstruction, to enhance model performance. Focus on real-world impact with a balance of online (in-car) and offline (data generation) work in a fast-paced, product-driven environment.

Wayve London, United Kingdom
Hybrid Permanent
See all 47 roles →
Top hirers

Companies hiring machine learning 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
23 open

Cambridge

Location
6 open

Oxford

Location
3 open

Manchester

Location
1 open
FAQs

Common questions

  • Essential skills include programming (especially Python), mathematics, statistics, and a deep understanding of machine learning algorithms and frameworks.

  • Gain relevant skills through courses and projects, and consider internships or junior roles to build practical experience.

  • Responsibilities include developing and deploying machine learning models, collaborating with data scientists, and maintaining model performance.

  • Progression typically starts from Junior to Senior, then to Principal, with increasing responsibilities and leadership roles.

  • Salaries vary based on experience and location. For specific salary ranges, please refer to the salary section on this page.

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