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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
51
Salary range
£48k – £160k
Hiring companies
18
View 51 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

£48k – £160k

Based on advertised midpoints across the 78 priced listings posted 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
43
160
26 jobs
Senior
50
122
17 jobs
Lead
80
162
14 jobs
Skills & tools

What hiring managers ask for

% of 88 listings posted in the last 12 months that mention each skill, extracted from job descriptions.

Python
86%
Machine Learning
61%
PyTorch
43%
MLOps
36%
TensorFlow
35%
AWS
26%
Azure
26%
CI/CD
24%
SQL
20%
Kubernetes
20%
GCP
18%
Docker
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 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

51 live roles

See all 51 roles →
Faculty AI logo

Principal Machine Learning Engineer

This role involves leading the technical direction of high-impact AI projects, particularly within financial services, by designing scalable machine learning systems and providing expert guidance across teams and clients. The engineer will architect complex data science frameworks, solve cross-cutting technical challenges, and influence company-wide strategy. Emphasis is placed on robust, production-grade AI solutions and advancing technical excellence in regulated environments.

Faculty AI London, United Kingdom
Hybrid Permanent
PhysicsX logo

Principal Machine Learning Engineer

Develop and deploy machine learning models integrated with engineering simulation data, focusing on scalable pipelines and real-world deployment in high-fidelity physics environments. Work directly with customers to translate AI research into production-grade tools, using 3D data, time-series forecasting, and optimization models. Lead technical architecture, mentor teams, and travel on-site to support implementation across aerospace, energy, and advanced manufacturing sectors.

PhysicsX United Kingdom
Hybrid Permanent
W

Staff Machine Learning Engineer - Ops

This role focuses on ensuring the quality and safety of machine learning models throughout Wayve's training and release pipeline. The engineer will establish release standards, validate model performance between training phases, and collaborate with platform, CI/CD, and evaluation teams to improve reliability and efficiency. The position involves deep engagement with MLOps workflows, automation, and model delivery infrastructure in a high-impact, safety-critical environment.

Wayve London, United Kingdom

Lead Machine Learning Engineer - Retail

Lead Machine Learning Engineer to define technical direction and deliver complex AI solutions for retail clients. Design scalable ML systems, mentor engineering teams, and drive innovation through reusable tools and cloud-native architectures. Work in high-risk, ambiguous environments to solve real-world business problems with responsible AI.

Faculty London, United Kingdom
On-site Permanent
W

Senior Machine Learning Engineer, AI Performance

This role involves taking machine learning models from training to production deployment, focusing on optimising for real-world constraints like latency and memory. The engineer will collaborate closely with performance and inference teams to deliver efficient, deployable models for autonomous driving systems, using techniques such as quantisation and distillation. The position emphasizes hands-on iteration in PyTorch and cross-functional delivery in a high-ownership environment.

Wayve London, United Kingdom

Senior Machine Learning Engineer

Design, train, and optimise machine learning models using TensorFlow and TFX, building scalable production pipelines and deploying models into live environments. Monitor system performance and collaborate with engineering, data, and product teams to deliver impactful ML solutions. Focus is on end-to-end MLOps, from development through deployment and ongoing optimisation.

Maxwell Bond Marylebone High Street, London, United Kingdom £58,000 – £60,000 pa
PhysicsX logo

Senior Machine Learning Engineer

A Senior Machine Learning Engineer will lead the deployment of AI models into production environments for engineering and physics simulations, working closely with customers and cross-functional teams. The role involves building scalable ML pipelines, mentoring engineers, and translating R&D into practical tools using Python, PyTorch, and cloud/on-prem infrastructure. Frequent international travel and on-site collaboration are key aspects of the role.

PhysicsX London, United Kingdom

Principal Machine Learning Engineer

Develop and deploy advanced machine learning models for speech recognition, translating research into scalable production systems. Lead technical innovation, mentor engineering teams, and shape the long-term ML vision. Work across the full model lifecycle, from training and optimisation to deployment and best practices in MLOps and distributed systems.

Speechmatics London, United Kingdom
See all 51 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
27 open

Cambridge

Location
4 open

Edinburgh

Location
1 open

Oxford

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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