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Machine Learning Engineer Jobs

Engineers who build, train, and deploy machine learning models. A core role in the tech industry, driving innovation and solving complex problems.

Open roles
52
Salary range
£45k – £153k
Hiring companies
22
View 52 live roles → Get an alert

Machine Learning Engineers are at the heart of the tech revolution, combining software engineering with advanced data science to create intelligent systems. They work across a wide range of industries, from tech giants and scaleups to research-heavy startups and the larger consultancies. Their role involves designing, building, and deploying machine learning models that can process and learn from vast amounts of data, enabling applications from natural language processing to computer vision and beyond.

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 cross-functional teams.

  1. 01
    Design and implement machine learning models.
  2. 02
    Optimise algorithms for performance and scalability.
  3. 03
    Collaborate with data scientists and software engineers.
  4. 04
    Conduct experiments and validate results.
  5. 05
    Document and present findings to stakeholders.
  6. 06
    Stay updated with the latest research and tools.
Salary on the board

£45k – £153k

Based on advertised midpoints across the 73 priced listings posted in the last 12 months. Base salary only.

Salary visibility
3% of listings advertise a salary — up from 0% the year before.
By seniority
£k base
Mid
43
160
27 jobs
Senior
50
124
14 jobs
Lead
80
162
14 jobs
Skills & tools

What hiring managers ask for

% of 92 listings posted in the last 12 months that mention each skill, extracted from job descriptions.

Python
85%
Machine Learning
60%
PyTorch
43%
TensorFlow
36%
MLOps
36%
AWS
26%
Azure
25%
CI/CD
24%
SQL
21%
Kubernetes
20%
GCP
17%
Docker
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 software engineers.

  3. Level 3

    Senior Machine Learning Engineer

    5–8 yrs

    Lead the design and implementation of complex machine learning systems, guiding junior team members and driving innovation.

  4. Level 4

    Principal Machine Learning Engineer

    8+ yrs

    Strategise and oversee the machine learning initiatives of an organisation, influencing the direction of projects and mentoring the team.

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 working on real-world projects. This could be through internships, personal projects, or open-source contributions.

  3. 3

    Gain Industry Experience

    Start your career as a Junior Machine Learning Engineer, working on smaller projects and learning from more experienced colleagues.

  4. 4

    Specialise and Advance

    Develop expertise in specific areas of machine learning, such as deep learning or reinforcement learning. Take on more complex projects and leadership roles.

  5. 5

    Lead and Innovate

    As a Senior or Principal Machine Learning Engineer, lead major projects, mentor junior team members, and drive innovation within your organisation.

Live jobs

52 live roles

See all 52 roles →
Faculty AI logo

Machine Learning Engineer

Develop and deploy production-grade machine learning systems for high-impact clients, particularly in the defence sector. Design scalable ML infrastructure, lead technical architecture decisions, and translate complex AI concepts for stakeholders. Work across the full ML lifecycle using cloud platforms and containerisation technologies.

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

Machine Learning Engineer

A Machine Learning Engineer will collaborate with simulation engineers and customers to solve complex physics and engineering challenges using AI. The role involves building scalable ML pipelines, working with 3D point-cloud and mesh data, and translating R&D into deployable tools. Engineers will also travel to customer sites globally to implement solutions on-site, ensuring practical, impactful delivery across industries like aerospace, energy, and semiconductors.

PhysicsX England £150,000 – £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, rapidly prototyping and deploying models into functional hardware systems. The role emphasizes innovation, rapid iteration, 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

This role involves deploying machine learning models and engineering surrogates—such as deep learning on CAE/CFD/FEA data, time-series forecasting, and anomaly detection—into customer production environments. The engineer will work closely with data scientists, simulation engineers, and clients across aerospace, energy, semiconductors, and automotive industries to build scalable, geometry-aware ML systems using 3D point-cloud and mesh data. Key responsibilities include designing robust training and inference pipelines, mentoring junior staff, and traveling to customer sites globally to implement AI-driven simulation solutions on-site.

PhysicsX United Kingdom
On-site Permanent

Machine learning Engineer

This role involves building and deploying production-grade machine learning systems for clients across energy, infrastructure, and government sectors. The engineer will work on scalable ML solutions, define best practices for deployment, and collaborate with cross-functional teams to deliver real-world AI impact. Emphasis is placed on operationalising models, cloud infrastructure, and translating technical concepts for non-technical stakeholders.

Faculty London, United Kingdom
Hybrid Permanent Clearance Required

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

Design and optimize machine learning models for hardware acceleration on platforms such as GPUs and QPUs, focusing on low-latency distributed systems and algorithm development. Work closely with international clients using cutting-edge simulation and modeling technologies. Operate as a senior individual contributor within an established engineering team.

Hexwired Recruitment Limited London, United Kingdom £80,000 – £120,000 pa

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 scalable MLOps infrastructure. The engineer will design CI/CD pipelines for ML artifacts, implement monitoring and security controls, and support real-time inference workloads. Collaboration with data scientists, developers, and architects is key to optimizing model performance and platform reliability.

Queen Square Recruitment Wokingham, Berkshire, United Kingdom £460 pd
See all 52 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
26 open

Cambridge

Location
7 open

Oxford

Location
3 open

Edinburgh

Location
2 open
FAQs

Common questions

  • Essential skills include programming (Python, R), mathematics (linear algebra, calculus), statistics, and knowledge of machine learning frameworks (TensorFlow, PyTorch).

  • Data Scientists focus on extracting insights from data, while Machine Learning Engineers build and deploy the models that power these insights. The roles often work closely together.

  • Responsibilities include designing and implementing machine learning models, optimising algorithms, collaborating with cross-functional teams, and staying updated with the latest research.

  • Salary ranges can vary widely based on experience, location, and industry. For more detailed information, refer to the salary section on this page.

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