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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
48
Salary range
£49k – £160k
Hiring companies
21
View 48 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

£49k – £160k

Based on advertised midpoints across the 89 UK listings priced in pounds in the last 12 months. Base salary only.

Salary visibility
5% of listings advertise a salary — up from 0% the year before.
By seniority
£k base
Mid
43
160
26 jobs
Senior
50
126
20 jobs
Lead
80
150
16 jobs
Skills & tools

What hiring managers ask for

% of 87 listings posted in the last 12 months that mention each skill, extracted from job descriptions.

Python
86%
Machine Learning
61%
PyTorch
43%
TensorFlow
36%
MLOps
36%
AWS
25%
Azure
25%
CI/CD
23%
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

48 live roles

See all 48 roles →

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

Machine Learning Engineer

As a Machine Learning Engineer in Delivery, you will work closely with customers and internal teams to design, build, and test reliable, scalable ML pipelines. You will deploy production-grade tools, manipulate 3D data, and integrate models with simulations, traveling to customer sites for on-site collaboration.

PhysicsX London, United Kingdom

Machine Learning Engineer

A Machine Learning Engineer will collaborate with simulation engineers, data scientists, and customers to develop AI-driven solutions for engineering and manufacturing challenges. The role involves building scalable ML pipelines, working with 3D point-cloud and mesh data, and translating R&D into deployable tools. The position requires strong software engineering practices and customer-facing delivery, with opportunities for international travel.

PhysicsX United Kingdom £150,000 – £190,000 pa
Remote 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 and evaluation systems. You will work on LangGraph, LangChain, and RAG pipelines, focusing on cost, latency, and auditability.

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

Machine Learning Engineer

Design and deploy production-grade machine learning systems for high-impact clients in national security and AI safety. Work across the full ML lifecycle, from prototyping to scalable deployment, using cloud infrastructure and modern MLOps practices. Collaborate with cross-functional teams to deliver secure, reliable AI solutions that solve real-world challenges.

Faculty London, United Kingdom
Hybrid Permanent

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 by developing and validating physics-informed models for ship resistance, propulsion performance, and energy efficiency. The engineer will also design and implement multidisciplinary optimization methods and extend NeuralShipper’s capabilities to wind-assisted propulsion systems.

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 48 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
29 open

Cambridge

Location
2 open

Manchester

Location
1 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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