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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
43
Salary range
£49k – £160k
Hiring companies
21
View 43 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

£49k – £160k

Based on advertised midpoints across the 80 UK listings priced in pounds in the last 12 months. Base salary only.

Salary visibility
4% of listings advertise a salary — up from 0% the year before.
By seniority
£k base
Mid
45
160
22 jobs
Senior
50
122
18 jobs
Lead
80
156
15 jobs
Skills & tools

What hiring managers ask for

% of 80 listings posted in the last 12 months that mention each skill, extracted from job descriptions.

Python
88%
Machine Learning
63%
PyTorch
46%
TensorFlow
38%
MLOps
36%
AWS
28%
Azure
26%
Kubernetes
24%
CI/CD
23%
GCP
20%
Docker
20%
SQL
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

43 live roles

See all 43 roles →

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

Machine Learning Engineer

Develop and deploy scalable machine learning systems integrated with high-fidelity physics simulations, working directly with customers and engineering teams to solve real-world industrial challenges. Focus on building reliable data pipelines, manipulating 3D point-cloud and mesh data, and translating research into production-grade tools. The role involves significant customer collaboration, on-site problem solving, and travel across multiple regions.

PhysicsX United Kingdom £150,000 – £190,000 pa
Remote Permanent

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

Machine Learning Engineer

This role involves building and deploying production-grade machine learning systems for high-impact clients in national security and AI safety. The engineer will lead technical architecture decisions, operationalise models using frameworks like TensorFlow and PyTorch, and develop scalable ML infrastructure. Collaboration with cross-functional teams and direct client engagement are key, with a focus on translating complex AI concepts into real-world solutions.

Faculty London, United Kingdom
Hybrid Permanent

Machine Learning Engineer

This role involves hands-on development of machine learning and language model workflows, integrating with various providers, and building robust retrieval systems. You will work on cost optimization, data privacy, and continuous improvement of the system's performance and reliability.

Maxwell Bond King's Cross, London, WC1H 8AL, United Kingdom £150,000 – £175,000 pa

Machine Learning Engineer

This role involves deploying and testing computer vision and ML systems in live environments, turning research models into production-grade software, and planning specialized data collections. You will also brief non-technical stakeholders on the capabilities and limitations of the technology.

CONVENTUS SOLUTIONS LIMITED Cyprus
University of Southampton logo

Machine Learning Engineer – Ship Design & Hydrodynamics (KTP Associate)

The role involves translating research into commercial solutions, developing physics-informed models for ship performance, and integrating these into NeuralShipper, a platform for automated vessel design. The engineer will work on multidisciplinary optimization and wind-assisted propulsion systems, collaborating with industry stakeholders.

University of Southampton Southampton, Hybrid, South East England, United Kingdom £41 – £45 pa
Contract

Machine Learning Engineer (Safety)

As a Machine Learning Engineer, you will build and deploy production-grade ML systems, collaborate with cross-functional teams to solve critical client challenges, and lead technical scoping and architectural decisions. You will work on high-stakes, high-impact missions in national security and AI safety, ensuring AI is secure, trustworthy, and safe for all.

Faculty London, United Kingdom
Hybrid Permanent
See all 43 roles →
Hiring locations

Where this role is hiring

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

London

Location
22 open

Cambridge

Location
2 open

Manchester

Location
1 open

Bristol

Location
1 open

Southampton

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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