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Machine Learning Engineer Jobs

Engineers who build and deploy machine learning models. A core role in the AI ecosystem, combining software engineering with data science.

Open roles
49
Salary range
£45k – £146k
Hiring companies
24
View 49 live roles → Get an alert

Machine Learning Engineers are at the heart of the AI revolution. They design, build, and deploy machine learning models that power everything from recommendation systems to autonomous vehicles. These roles are found in a wide range of organisations, from tech giants and research-heavy startups to scaleups and the larger consultancies. The work is highly technical, requiring a deep understanding of both software engineering and data science principles.

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 data scientists and other engineers.

  1. 01
    Develop and optimise machine learning models.
  2. 02
    Collaborate with data scientists to refine datasets.
  3. 03
    Integrate models into production systems.
  4. 04
    Monitor and maintain model performance.
  5. 05
    Document and present findings to the team.
  6. 06
    Stay updated with the latest research and tools.
Salary on the board

£45k – £146k

Based on advertised midpoints across the 65 priced listings posted in the last 12 months. Base salary only.

Salary visibility
2% of listings advertise a salary — up from 0% the year before.
By seniority
£k base
Mid
45
160
24 jobs
Senior
50
124
14 jobs
Lead
80
168
13 jobs
Skills & tools

What hiring managers ask for

% of 82 listings posted in the last 12 months that mention each skill, extracted from job descriptions.

Python
87%
Machine Learning
62%
PyTorch
48%
TensorFlow
37%
MLOps
37%
AWS
27%
Azure
26%
Kubernetes
24%
CI/CD
23%
Docker
21%
SQL
20%
GCP
20%
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 other engineers.

  3. Level 3

    Senior Machine Learning Engineer

    5–8 yrs

    Lead the design and implementation of complex machine learning systems, mentoring junior engineers and driving innovation.

  4. Level 4

    Principal Machine Learning Engineer

    8+ yrs

    Strategise and oversee the AI roadmap, influencing the direction of the organisation's machine learning efforts and leading large teams.

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 building machine learning projects. This could be through personal projects, internships, or university coursework.

  3. 3

    Gain Industry Experience

    Start your career as a Junior Machine Learning Engineer, working on real-world problems and learning from experienced colleagues.

  4. 4

    Specialise and Advance

    Develop expertise in specific areas of machine learning, such as natural language processing or computer vision. Progress to more senior roles.

  5. 5

    Lead and Innovate

    Take on leadership roles, driving the development of cutting-edge AI solutions and mentoring the next generation of machine learning engineers.

  6. 6

    Influence Strategy

    Shape the AI strategy of your organisation, influencing key decisions and leading large-scale machine learning initiatives.

Live jobs

49 live roles

See all 49 roles →
PhysicsX logo

Machine Learning Engineer

Develop and deploy scalable machine learning systems integrated with high-fidelity physics simulations, working directly with customers and engineering teams to solve real-world industrial challenges. Focus on building reliable data pipelines, manipulating 3D point-cloud and mesh data, and translating research into production-grade tools. The role involves significant customer collaboration, on-site problem solving, and travel across multiple regions.

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 with a balance of online (in-car) and offline (data generation) work in a fast-paced, product-driven environment.

Wayve London, United Kingdom
Hybrid Permanent
W

Machine Learning Engineer, Performance Tooling

Build and scale performance tooling for AI systems across cloud and embedded hardware, focusing on profiling, prediction, and optimization of deep learning models. Analyze bottlenecks across the full AI stack—from models to accelerators—and deliver data-driven insights to guide performance decisions. Collaborate with cross-functional teams to establish standards and drive efficiency in model training and inference.

Wayve United Kingdom

Machine Learning Engineer, Platform

This role involves building and owning end-to-end machine learning components within a generative AI platform, with a focus on retrieval systems, knowledge representation, and RAG pipelines. The engineer will design and implement systems for knowledge retrieval, vector indexing, and context engines that power enterprise AI agents. Work includes developing evaluation frameworks, integrating with enterprise data sources, and collaborating across ML, product, and infrastructure teams to deliver high-impact AI solutions.

Scale AI London, United Kingdom
Hybrid Permanent

Machine Learning Engineer, Global Public Sector

Design and build reliable, multi-step agentic systems for high-stakes government applications, focusing on AI safety, red-teaming, and model optimization in regulated environments. Develop novel architectures and evaluation frameworks to ensure sovereign AI systems are performant, unbiased, and production-ready at scale.

Scale AI United Kingdom
On-site Permanent Clearance Required
Faculty AI logo

Senior Machine Learning Engineer

Lead the development and deployment of cutting-edge, production-grade machine learning systems for high-impact clients, particularly in the defence sector. Design scalable ML infrastructure, define best practices for ML deployment, and act as a technical advisor while mentoring junior engineers. Work in a cross-functional environment with strong emphasis on ethical, reliable AI and client collaboration.

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

Lead Machine Learning Engineer

Leads the technical direction and delivery of complex machine learning projects, designing scalable and reliable AI systems while guiding architectural decisions and mentoring engineering teams. Focuses on building reusable solutions and driving innovation within regulated environments across financial services and other sectors. Works closely with clients and stakeholders to translate strategic goals into practical, high-impact AI implementations.

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 simulation, working closely with customers and cross-functional teams. The role involves building scalable ML pipelines, mentoring engineers, and traveling to client sites to implement solutions on-site. The position focuses on turning research into practical, high-impact tools using Python, PyTorch, and cloud/on-prem infrastructure.

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

Cambridge

Location
5 open

Oxford

Location
1 open
FAQs

Common questions

  • Essential skills include programming (especially Python), mathematics, statistics, and a deep understanding of machine learning algorithms and frameworks.

  • Gain relevant skills through courses and projects, and consider internships or junior roles to build practical experience.

  • Responsibilities include developing and deploying machine learning models, collaborating with data scientists, and maintaining model performance.

  • Progression typically starts from Junior to Senior, then to Principal, with increasing responsibilities and leadership roles.

  • Salaries vary based on experience and location. For specific salary ranges, please refer to the salary section on this page.

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