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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 →
PhysicsX logo

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
W

Machine Learning Engineer, ADAS

Train and improve computer vision and 3D perception models for ADAS systems, working across the full ML lifecycle from data to deployment. Build scalable data pipelines, including auto-labelling and 3D reconstruction, to enhance model performance. Focus on real-world impact by iterating on detection, classification, and segmentation for lanes, objects, and traffic infrastructure.

Wayve London, United Kingdom
Hybrid Permanent
Newton Colmore logo

Machine Learning Engineer Modelling - Remote Work

Machine Learning Engineer - Hybrid Modelling - Remote / HybridNewton Colmore is partnered with a venture-backed deep tech company developing novel intelligent systems that will transform how complex industrial and scientific processes are designed, monitored, and optimised. This will be...

Newton Colmore Spain, United Kingdom
Hybrid
W

Machine Learning Engineer, Performance Tooling

Builds performance analysis tools to optimize AI models across the full stack, from compilers to hardware. Measures, predicts, and advises on latency, throughput, and compute efficiency using profiling data. Works cross-functionally with model, runtime, and hardware teams to drive data-informed performance decisions.

Wayve United Kingdom

Machine Learning Engineer - Quantitative Trading- Leading Market-Maker / Hedge Fund

Design and build machine learning infrastructure for training, inference, and large-scale research workflows in a high-performance trading environment. Collaborate with researchers and engineers to productionise ML models and improve experimentation tooling. Work at the intersection of software engineering, mathematics, and cutting-edge ML systems.

eFinancialCareers London, United Kingdom £200,000 – £250,000 pa
Faculty AI logo

Senior Machine Learning Engineer

Lead the design and deployment of production-grade machine learning systems for high-impact clients, particularly in the defence sector. Focus on scalable, ethical AI solutions using cloud platforms and modern MLOps practices. Mentor junior engineers and shape engineering standards while working across technical, product, and client teams.

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

Lead Machine Learning Engineer

Lead Machine Learning Engineer to define technical direction for complex AI projects, design scalable ML systems, and guide delivery across high-risk, ill-defined environments. Will lead architectural decisions, mentor engineers, develop reusable tools, and act as a technical advisor to clients in regulated sectors. Focus on operationalising models using Python and major cloud platforms with containerised deployment via Docker and Kubernetes.

Faculty AI London, United Kingdom
Hybrid Permanent
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 traveling globally to co-develop solutions on-site. The engineer will work with 3D data, CAE/CFD/FEA models, and time-series forecasting, translating R&D into robust, reusable tools.

PhysicsX England US$200,000 – US$250,000 pa
On-site Permanent Clearance Required
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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