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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
49
Salary range
£35k – £160k
Hiring companies
17
View 49 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

£35k – £160k

Based on advertised midpoints across the 27 priced listings posted in the last 12 months. Base salary only.

By seniority
£k base
Entry
39
40
1 job
Junior
69
83
1 job
Mid
35
160
13 jobs
Senior
50
110
4 jobs
Lead
90
120
2 jobs
Skills & tools

What hiring managers ask for

% of 50 listings posted in the last 12 months that mention each skill, extracted from job descriptions.

Python
82%
Machine Learning
70%
PyTorch
60%
TensorFlow
52%
AWS
36%
MLOps
32%
Azure
26%
GCP
26%
Kubernetes
26%
Docker
24%
Data Pipelines
14%
Scikit-learn
14%
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

49 live roles

See all 49 roles →
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 work on diverse projects from AI strategy to client-side deployments, ensuring architectural decisions are sound and driving innovation across the organisation.

Faculty AI London, United Kingdom
Hybrid Permanent
PhysicsX logo

Staff Machine Learning Software Engineer, Research

This role involves leading machine learning engineering efforts within a research context, focusing on transforming experimental models into scalable, production-grade systems for physics-informed AI simulations. The engineer will work closely with research scientists to design and optimise distributed training architectures, build foundation models, and deliver robust ML solutions for complex engineering problems. A strong emphasis is placed on mentorship, technical leadership, and translating cutting-edge research into reusable software tools and products.

PhysicsX London, United Kingdom
On-site Permanent
PhysicsX logo

Principal Machine Learning Infrastructure Engineer

About us PhysicsX is a deep-tech company with roots in numerical physics and Formula One, dedicated to accelerating hardware innovation at the speed of software. We are building an AI-driven simulation software stack for engineering and manufacturing across advanced industries....

PhysicsX London, United Kingdom

Research Engineer, Machine Learning (RL Velocity)

As a Research Engineer on the RL Velocity team, you will focus on building and improving the RL training infrastructure, identifying and removing bottlenecks, and partnering with researchers and engineering teams to enhance the efficiency and reliability of Anthropic's AI systems. This role involves high-leverage work that impacts the entire organization's ability to iterate and improve models quickly.

Anthropic London, United Kingdom £370,000 – £630,000 pa
Hybrid Permanent
See all 49 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
22 open

Cambridge

Location
4 open

Oxford

Location
2 open

Birmingham

Location
1 open

Portsmouth

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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