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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
36
Salary range
£35k – £200k
Hiring companies
20
View 36 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

£35k – £200k

Based on advertised midpoints across the 29 priced listings posted in the last 12 months. Base salary only.

By seniority
£k base
Entry
39
40
1 job
Mid
35
160
15 jobs
Senior
50
160
7 jobs
Lead
81
200
4 jobs
Skills & tools

What hiring managers ask for

% of 59 listings posted in the last 12 months that mention each skill, extracted from job descriptions.

Python
85%
PyTorch
63%
Machine Learning
61%
TensorFlow
49%
AWS
32%
MLOps
32%
GCP
27%
Kubernetes
27%
Docker
25%
Azure
22%
Computer Vision
19%
Scikit-learn
15%
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

36 live roles

See all 36 roles →
Faculty AI logo

Machine Learning Engineer

This role involves building and deploying production-grade machine learning systems for high-impact clients, particularly in the defence sector. You'll work across the full ML lifecycle, from scoping and design to implementation, ensuring scalable, ethical AI solutions are delivered with technical excellence. Collaboration with cross-functional teams and direct client engagement are key aspects of the position.

Faculty AI London, United Kingdom
Remote Permanent Flexible 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

As a Machine Learning Engineer, you will collaborate with Data Scientists, Simulation Engineers, and customers to solve complex engineering and physics challenges. You will design, build, and test reliable, scalable ML data pipelines, manipulate 3D point cloud and mesh data, and ensure the successful deployment of AI models in real-world applications.

PhysicsX United Kingdom
Remote Permanent

Machine learning Engineer

Work as a Machine Learning Engineer building production-grade AI systems for clients in energy, sustainability, and public sectors. Focus on operationalising machine learning models, designing scalable infrastructure, and translating technical concepts for stakeholders. Collaborate across engineering, data science, and commercial teams to deliver real-world impact through responsible AI.

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

Job title: Machine Learning EngineerLocations: Manchester or Haywards Heath (hybrid working)Role overviewMarkerstudy Group are looking for a Machine Learning Engineer to help take leading-edge and novel insurance risk modelling and pricing techniques and participate in creating fully automated machine learning...

Vermelo RPO Manchester, United Kingdom

Machine Learning Engineer

This role involves developing and deploying automated machine learning pipelines for insurance risk modelling and pricing. The engineer will tune, refine, and maintain ML models using DevOps and MLOps practices, with a focus on high-quality, production-grade code and test-driven development. The position supports innovation across motor, home, and commercial insurance lines while mentoring junior engineers and promoting data science excellence.

Vermelo RPO M43Aq, M4 3AQ, United Kingdom
Hybrid Permanent
Wayve logo

Machine Learning Engineer, ADAS

Train, debug, 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. Collaborate to address real-world driving challenges with a focus on measurable impact and shipping.

Wayve London, United Kingdom
Hybrid Permanent
See all 36 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
18 open

Cambridge

Location
6 open

Oxford

Location
4 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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