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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
45
Salary range
£35k – £160k
Hiring companies
17
View 45 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 – £160k

Based on advertised midpoints across the 22 priced listings posted in the last 12 months. Base salary only.

By seniority
£k base
Entry
39
40
1 job
Mid
35
160
13 jobs
Senior
50
120
5 jobs
Lead
90
120
2 jobs
Skills & tools

What hiring managers ask for

% of 51 listings posted in the last 12 months that mention each skill, extracted from job descriptions.

Python
82%
Machine Learning
65%
PyTorch
63%
TensorFlow
53%
AWS
35%
Kubernetes
31%
GCP
29%
MLOps
29%
Docker
27%
Azure
24%
Pandas
16%
Scikit-learn
16%
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

45 live roles

See all 45 roles →
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 (Computer Vision)

This role involves designing, training, and deploying computer vision models across the full machine learning lifecycle. You will work closely with engineers, data scientists, and domain experts to build production-ready systems and evaluate model performance in complex real-world environments.

Platform Recruitment Oxford, Oxfordshire, United Kingdom £85,000 – £160,000 pa
On-site Permanent

Machine Learning Engineer (Computer Vision)

This role involves designing, training, and deploying computer vision models across the full machine learning lifecycle. You will work closely with engineers, data scientists, and domain experts to build production-ready systems and evaluate model performance in complex real-world environments.

Platform Recruitment Cambridge, Cambridgeshire, United Kingdom £85,000 – £160,000 pa
On-site Permanent
Faculty AI logo

Senior Machine Learning Engineer

As a Senior Machine Learning Engineer, you will lead the development and deployment of cutting-edge AI systems for diverse clients, focusing on high-impact ML systems, production-grade software, and scalable infrastructure. You will collaborate with cross-functional teams, mentor junior engineers, and act as a trusted technical advisor to clients.

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

Lead Machine Learning Engineer

As a Lead Machine Learning Engineer, you will set the technical direction for complex AI projects, design and implement scalable ML systems, and lead a team of engineers. You will drive innovation, mentor team members, and act as a technical expert for clients, ensuring the successful delivery of high-impact AI solutions in a regulated environment.

Faculty AI London, United Kingdom
Hybrid Permanent
PhysicsX logo

Senior Machine Learning Engineer

As a Senior Machine Learning Engineer, you will lead the deployment of AI models and engineering surrogates into customer production environments, working closely with Data Scientists, Simulation Engineers, and customers. You will mentor team members, travel to customer sites, and influence product direction by driving reliable and scalable ML systems.

PhysicsX North Tyneside, NE29 8EP, United Kingdom
On-site Permanent Clearance Required

Senior Machine Learning Engineer

Lead the development and deployment of machine learning models from problem definition through to production, working with real-world operational data. Focus on rigorous experimentation, statistical reasoning, and integration within secure, regulated environments. Collaborate across technical and non-technical stakeholders to deliver impactful, well-engineered solutions.

Guidant Global London, City And County Of the City Of London, United Kingdom £700 – £900 pd
Hybrid Permanent Clearance Required

Lead Machine Learning Engineer - Retail

As a Lead Machine Learning Engineer, you will set the technical direction for complex AI projects, design and maintain scalable ML systems, and lead a team of engineers. You will also drive innovation, mentor team members, and act as a technical expert for clients, ensuring successful project delivery and adoption of new technologies.

Faculty London, United Kingdom
On-site Permanent
See all 45 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
16 open

Cambridge

Location
5 open

Oxford

Location
2 open

Birmingham

Location
1 open

Portsmouth

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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