1,014 Lead AI Engineer jobs in the United Kingdom
Lead AI Engineer - Cloud & Platform Services
Posted 3 days ago
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Job Description
**Job Title:** **Lead AI Engineer - Cloud & Platform Services**
**Location:** Cambridge, UK (Hybrid)
**Employment Type:** Regular, Full-Time
**Reports To:** R&D Senior Manager
We are looking for passionate and skilled Software Developers to join our Core AI Services team. In this role, you will help design, develop, and scale AI-enabling platform services and public APIs that are secure, reliable, and cloud-native. These services will act as foundational building blocks for AI adoption across AVEVA's product portfolio and partner ecosystem.
You will part of a Scrum team to build innovative, standards-compliant, secure and production-grade AI capabilities, with a builder mindset - rapid prototyping and continuous improvement with agility of a start-up.
**Key Responsibilities:**
+ Build scalable, fault-tolerant cloud-native services on Microsoft Azure, ensuring high performance and reliability.
+ Develop secure, well-documented public APIs and SDKs for consumption by internal and external developers.
+ Collaborate with cross-functional teams to deliver end-to-end solutions across data pipelines, orchestration, and service APIs.
+ Embed robust security controls to protect sensitive data and ensure secure access to AI services.
+ Contribute to design reviews, code reviews, and architectural discussions to ensure engineering excellence.
+ Mentor junior developers, encourage continuous learning, and contribute to a culture of innovation.
+ Work with multiple teams to create AI solutions, which include AI model deployment, training, and AI tooling development.
**AI & Cloud Expertise**
+ Experience working with Large Language Models (LLMs) and understanding of trade-offs between performance, cost, and capability.
+ Understanding of Retrieval-Augmented Generation (RAG), agent orchestration, prompt engineering, and tool calling.
+ Familiarity with AI standards such as Model Context Protocol (MCP) and Agent2Agent (A2A).
+ Strong knowledge or experience in working with various ML algorithms (regression, classification, clustering, deep learning)
+ Knowledge of AI ethics and regulations (e.g., NIST AI RMF, EU AI Act), and commitment to responsible AI development.
+ Fluent in developing code using AI Tools such as GitHub Copilot. Must be able to use prompt engineering to carry out multiple development tasks.
+ Familiar with AI orchestration, including tools like AI Foundry and/or Semantic Kernel.
+ Experience with tools for automated testing and evaluation of AI outputs is a plus.
+ Experience in Python and AI frameworks / tools such as PyTorch and TensorFlow.
**Core Skills and Qualifications:**
+ 8+ years of professional software engineering experience, including 3+ years working directly on AI/ML systems or platforms.
+ Hands-on experience with Microsoft Azure and associated PaaS services (e.g., Azure Functions, AKS, API Management).
+ Strong expertise in RESTful API design, versioning, testing, and lifecycle management.
+ Proficient in securing APIs, managing authentication/authorization and data privacy practices.
+ Excellent problem-solving skills, with the ability to analyse complex technical challenges and propose scalable solutions.
+ Experience working in Agile teams and collaborating across global R&D locations
+ Demonstrated ability to mentor junior team members fostering a culture of continuous learning and innovation
+ Demonstrated experience with AI frameworks, tools and Python
**R&D at AVEVA**
Our global team of 2000+ developers work on an incredibly diverse portfolio of over 75 industrial automation and engineering products, which cover everything from data management to 3D design. AI and cloud are at the centre of our strategy, and we have over 150 patents to our name.
Our track record of innovation is no fluke - it's the result of a structured and deliberate focus on learning, collaboration and inclusivity. If you want to build applications that solve big problems, join us.
Find out more: aveva.com/en/about/careers/r-and-d-careers/
**Why Join AVEVA?**
At AVEVA, we are unlocking the power of industrial intelligence to create a more sustainable and efficient world. AVEVA Connect platform is at the heart of that transformation. As a leader in Core AI Services, you will help shape how AI is delivered at scale across industries. Join us in driving the next wave of industrial innovation.
**UK Benefits include:**
Flexible benefits fund, emergency leave days, adoption leave, 28 days annual leave (plus bank holidays), pension, life cover, private medical insurance, parental leave, education assistance program.
It's possible we're hiring for this position in multiple countries, in which case the above benefits apply to the primary location. Specific benefits vary by country, but our packages are similarly comprehensive.
Find out more: aveva.com/en/about/careers/benefits/
**Hybrid working**
By default, employees are expected to be in their local AVEVA office three days a week, but some positions are fully office-based. Roles supporting particular customers or markets are sometimes remote.
**Hiring process**
Interested? Great! Get started by submitting your cover letter and CV through our application portal. AVEVA is committed to recruiting and retaining people with disabilities. Please let us know in advance if you need reasonable support during your application process.
Find out more: aveva.com/en/about/careers/hiring-process
**About AVEVA**
AVEVA is a global leader in industrial software with more than 6,500 employees in over 40 countries. Our cutting-edge solutions are used by thousands of enterprises to deliver the essentials of life - such as energy, infrastructure, chemicals, and minerals - safely, efficiently, and more sustainably.
We are committed to embedding sustainability and inclusion into our operations, our culture, and our core business strategy. Learn more about how we are progressing against our ambitious 2030 targets: sustainability-report.aveva.com/
Find out more: aveva.com/en/about/careers/
AVEVA requires all successful applicants to undergo and pass a drug screening and comprehensive background check before they start employment. Background checks will be conducted in accordance with local laws and may, subject to those laws, include proof of educational attainment, employment history verification, proof of work authorization, criminal records, identity verification, credit check. Certain positions dealing with sensitive and/or third-party personal data may involve additional background check criteria.
AVEVA is an Equal Opportunity Employer. We are committed to being an exemplary employer with an inclusive culture, developing a workplace environment where all our employees are treated with dignity and respect. We value diversity and the expertise that people from different backgrounds bring to our business. AVEVA provides reasonable accommodation to applicants with disabilities where appropriate. If you need reasonable accommodation for any part of the application and hiring process, please notify your recruiter. Determinations on requests for reasonable accommodation will be made on a case-by-case basis.
Empowering you with pioneering tech
AVEVA is a global leader in industrial software. Our cutting-edge solutions are used by thousands of enterprises to deliver the essentials of life - such as energy, infrastructure, chemicals and minerals - safely, efficiently and more sustainably.
We're the first software business in the world to have our sustainability targets validated by the SBTi, and we've been recognized for the transparency and ambition of our commitment to diversity, equity, and inclusion. We've also recently been named as one of the world's most innovative companies.
If you're a curious and collaborative person who wants to make a big impact through technology, then we want to hear from you! Find out more at AVEVA Careers ( .
For more information about our privacy policy and how to manage cookies, visit our Privacy Policy ( .
Freelance AI Trainer (Artificial Intelligence & Machine Learning)
Posted 6 days ago
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Job Description
£400 - £500 per day | Remote / UK-Based | Contract / Freelance
Are you an expert in Artificial Intelligence (AI) and Machine Learning (ML) looking for flexible freelance opportunities? We are seeking an experienced AI Trainer to deliver AI and Machine Learning training courses to professionals and organisations across the UK.
As part.
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Machine Learning Engineer
Posted 2 days ago
Job Viewed
Job Description
Role: Machine Learning Operations Engineer
Location: Oxfordshire
Salary: 65,000 - 75,000
This is an exciting opportunity to join a world leading company specialising in motion capture and tracking systems, with products used globally in the entertainment, engineering, and life sciences sectors. My Client are looking for a talented Machine Learning Operations Engineer to support and enhance their cutting edge machine learning capabilities.
The Role
You will join a collaborative Research and Development team based in Oxford, contributing to the development and maintenance of a modern ML operations stack. This includes data acquisition pipelines, data management, and machine learning model training infrastructure. The environment includes both self-managed on premise systems and cloud-based infrastructure, primarily using AWS.
You will have the opportunity to influence the technical direction of the ML Ops team, propose new areas for development, and potentially lead your own projects.
This is a hybrid role combining remote and on site working. There is no expectation to be available outside core business hours.
Key Responsibilities
- Maintain and improve ML Ops infrastructure
- Manage on premise Kubernetes clusters and ML pipelines
- Integrate ML toolkits into operational workflows
- Collaborate with ML developers to streamline workflows
- Suggest and implement technical improvements and new tools
Required Skills and Experience
- Academic background (research Masters level) or industry experience in a relevant field
- Strong experience managing on premise Kubernetes clusters
- Deep knowledge of Kubeflow or similar systems such as MLflow
- Proficient in Python and experienced with Linux systems
- Familiar with AWS services such as Cognito, S3, EC2 and Lambda
- Experience working with ML frameworks such as PyTorch or Lightning
- Capable of designing and delivering ML Ops solutions across various platforms
Desirable Skills
- Background in DevOps with experience in CI systems such as Jenkins
- Familiarity with infrastructure as code tools such as Ansible
- Interest in human motion capture, sports tech, or animation
- Exposure to C++ is a bonus
Benefits
- 65,000 - 75,000 (DOE)
- 10 percent company pension
- 25 days annual leave plus bank holidays
- Life assurance
- Private medical insurance including dental and optical
- Permanent health insurance
- Cycle to work scheme
- Free on site parking
WR Engineering are the #1 recruitment partner for engineering, manufacturing & technical sales jobs. We recruit for permanent and contract jobs UK wide.
WR is acting as an Employment Agency in relation to this vacancy.
Machine Learning Engineer
Posted 2 days ago
Job Viewed
Job Description
Job Description:
We are seeking an experienced Machine Learning Engineer with expertise in big programmes and has contributed to the delivery of complex business cloud solutions. The ideal candidate will have a strong background in Machine Learning engineering and an expert in operationalising models in the Databricks MLFlow environment (chosen MLOps Platform).
Responsibilities:
- Collaborate with Data Scientists and operationalize the model with auditing enabled, ensure the run can be reproduced if needed. li>Implement Databricks best practices in building and maintaining economic modelling (Machine Learning) pipelines.
- Ensure the models are modular. Ensure the model is source-controlled with agreed release numbering.
- Extract any hard-coded elements and parameterise them so that the model execution can be controlled through input parameters.
- Ensure the model input parameters are version-controlled and logged to the model execution runs for auditability.
- Ensure model metrics are logged to the model runs.
- Ensure model logging, monitoring, and alerting to make sure any failure points are captured, monitored and alerted for support team to investigate or re-run of the model involves running of multiple experiments and choosing the best model (champion challenger) based on the accuracy/error rate of each experiment, ensure this is done in an automated manner. li>Ensure the model is triggered to run as per the defined schedule. If the process involves executing multiple models feeding each other to produce the final business outcome, orchestrate them to run based on the defined dependencies.
- Define and Maintain the ML Frameworks (Python, R & MATLAB templates) with any common reusable code that might emerge as part of model developments/operationalisation for future
- models to benefit.
- Where applicable, capture data drift, concept drift, model performance degradation signals and ensure model retrain.
- Implement CI/CD pipelines for ML models and automate the deployment.
- Maintain relevant documentation.
Requirements:
- Bachelor's degree in a relevant field.
- Minimum of 5 years of experience as a business analyst, with a focus on capturing and documenting business requirements and business processes.
- Strong understanding of banking and financial industry practices and regulations.
- Solid knowledge of Data Management process, data analysis and modelling techniques.
- Experience in monetary policy analysis (nice to have)
- Experience in time series database analysis
- Familiarity with business intelligence tools and concepts.
- Strong analytical and problem-solving skills.
- Experience in managing software development lifecycles within Agile frameworks to ensure timely and high-quality delivery.
- Excellent communication and collaboration skills.
- Ability to adapt to changing requirements and priorities in a fast-paced environment.
Machine Learning Engineer
Posted 2 days ago
Job Viewed
Job Description
Spearheading the integration of machine learning into cutting-edge electronics
This innovative team of engineers and scientists are using machine learning tightly integrated with modern electronics to create new classes of products and radically alter the shape, performance and effectiveness of existing ones. As industry goes through a machine learning revolution you can be here, leading the charge.
You will work across the whole machine learning development lifecycle from initial concepts through data collection, cleaning and preparation to prototyping, testing and evaluation. With your models integrated with leading edge electronics, the final products are fully functional prototypes and demonstrator units manufactured at small scale. What’s special about this group is they do this dozens of times per year working across multiple domains. You can be working on computer vision for one project and generative models for the next.
Requirements:
- Strong knowledge of Python and its use in machine learning including hands-on experience building products with modern ML frameworks such as TensorFlow and PyTorch li>Broad knowledge of machine learning techniques across multiple domains and the ability to transition into new domains quickly
- A top degree in a STEM subject
- UK national
While not required, experience deploying machine learning onto a range of hardware from resource constrained embedded systems through to edge computing is desirable. As is any knowledge of GPU programming languages and frameworks (CUDA, ROCm, etc).
Your future colleagues will be similarly highly skilled, with experience across industry and the drive to innovate. You will find yourself in a low-management work environment that encourages teamwork and respect for individuals’ expertise. Benefits include private medical insurance, generous pension scheme and access to local social and sports clubs. Please note, you are required to be onsite full-time for this position.
Another top job from ECM, the high-tech recruitment experts.
Even if this job's not quite right, do contact us now - we may well have the ideal job for you. To discuss your requirements call (phone number removed) or email your CV. We will always ask before forwarding your CV.
Please apply (quoting ref: CV27413 ) only if you are eligible to live and work in the UK. By submitting your details you certify that the information you provide is accurate.
Machine Learning Engineer
Posted 5 days ago
Job Viewed
Job Description
Job Description:
We are seeking an experienced Machine Learning Engineer with expertise in big programmes and has contributed to the delivery of complex business cloud solutions. The ideal candidate will have a strong background in Machine Learning engineering and an expert in operationalising models in the Databricks MLFlow environment (chosen MLOps Platform).
Responsibilities:
- Collaborate with Data Scientists and operationalize the model with auditing enabled, ensure the run can be reproduced if needed. li>Implement Databricks best practices in building and maintaining economic modelling (Machine Learning) pipelines.
- Ensure the models are modular. Ensure the model is source-controlled with agreed release numbering.
- Extract any hard-coded elements and parameterise them so that the model execution can be controlled through input parameters.
- Ensure the model input parameters are version-controlled and logged to the model execution runs for auditability.
- Ensure model metrics are logged to the model runs.
- Ensure model logging, monitoring, and alerting to make sure any failure points are captured, monitored and alerted for support team to investigate or re-run of the model involves running of multiple experiments and choosing the best model (champion challenger) based on the accuracy/error rate of each experiment, ensure this is done in an automated manner. li>Ensure the model is triggered to run as per the defined schedule. If the process involves executing multiple models feeding each other to produce the final business outcome, orchestrate them to run based on the defined dependencies.
- Define and Maintain the ML Frameworks (Python, R & MATLAB templates) with any common reusable code that might emerge as part of model developments/operationalisation for future
- models to benefit.
- Where applicable, capture data drift, concept drift, model performance degradation signals and ensure model retrain.
- Implement CI/CD pipelines for ML models and automate the deployment.
- Maintain relevant documentation.
Requirements:
- Bachelor's degree in a relevant field.
- Minimum of 5 years of experience as a business analyst, with a focus on capturing and documenting business requirements and business processes.
- Strong understanding of banking and financial industry practices and regulations.
- Solid knowledge of Data Management process, data analysis and modelling techniques.
- Experience in monetary policy analysis (nice to have)
- Experience in time series database analysis
- Familiarity with business intelligence tools and concepts.
- Strong analytical and problem-solving skills.
- Experience in managing software development lifecycles within Agile frameworks to ensure timely and high-quality delivery.
- Excellent communication and collaboration skills.
- Ability to adapt to changing requirements and priorities in a fast-paced environment.
Machine Learning Engineer
Posted 5 days ago
Job Viewed
Job Description
Role: Machine Learning Operations Engineer
Location: Oxfordshire
Salary: 65,000 - 75,000
This is an exciting opportunity to join a world leading company specialising in motion capture and tracking systems, with products used globally in the entertainment, engineering, and life sciences sectors. My Client are looking for a talented Machine Learning Operations Engineer to support and enhance their cutting edge machine learning capabilities.
The Role
You will join a collaborative Research and Development team based in Oxford, contributing to the development and maintenance of a modern ML operations stack. This includes data acquisition pipelines, data management, and machine learning model training infrastructure. The environment includes both self-managed on premise systems and cloud-based infrastructure, primarily using AWS.
You will have the opportunity to influence the technical direction of the ML Ops team, propose new areas for development, and potentially lead your own projects.
This is a hybrid role combining remote and on site working. There is no expectation to be available outside core business hours.
Key Responsibilities
- Maintain and improve ML Ops infrastructure
- Manage on premise Kubernetes clusters and ML pipelines
- Integrate ML toolkits into operational workflows
- Collaborate with ML developers to streamline workflows
- Suggest and implement technical improvements and new tools
Required Skills and Experience
- Academic background (research Masters level) or industry experience in a relevant field
- Strong experience managing on premise Kubernetes clusters
- Deep knowledge of Kubeflow or similar systems such as MLflow
- Proficient in Python and experienced with Linux systems
- Familiar with AWS services such as Cognito, S3, EC2 and Lambda
- Experience working with ML frameworks such as PyTorch or Lightning
- Capable of designing and delivering ML Ops solutions across various platforms
Desirable Skills
- Background in DevOps with experience in CI systems such as Jenkins
- Familiarity with infrastructure as code tools such as Ansible
- Interest in human motion capture, sports tech, or animation
- Exposure to C++ is a bonus
Benefits
- 65,000 - 75,000 (DOE)
- 10 percent company pension
- 25 days annual leave plus bank holidays
- Life assurance
- Private medical insurance including dental and optical
- Permanent health insurance
- Cycle to work scheme
- Free on site parking
WR Engineering are the #1 recruitment partner for engineering, manufacturing & technical sales jobs. We recruit for permanent and contract jobs UK wide.
WR is acting as an Employment Agency in relation to this vacancy.
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Machine Learning Engineer
Posted 5 days ago
Job Viewed
Job Description
Spearheading the integration of machine learning into cutting-edge electronics
This innovative team of engineers and scientists are using machine learning tightly integrated with modern electronics to create new classes of products and radically alter the shape, performance and effectiveness of existing ones. As industry goes through a machine learning revolution you can be here, leading the charge.
You will work across the whole machine learning development lifecycle from initial concepts through data collection, cleaning and preparation to prototyping, testing and evaluation. With your models integrated with leading edge electronics, the final products are fully functional prototypes and demonstrator units manufactured at small scale. What’s special about this group is they do this dozens of times per year working across multiple domains. You can be working on computer vision for one project and generative models for the next.
Requirements:
- Strong knowledge of Python and its use in machine learning including hands-on experience building products with modern ML frameworks such as TensorFlow and PyTorch li>Broad knowledge of machine learning techniques across multiple domains and the ability to transition into new domains quickly
- A top degree in a STEM subject
- UK national
While not required, experience deploying machine learning onto a range of hardware from resource constrained embedded systems through to edge computing is desirable. As is any knowledge of GPU programming languages and frameworks (CUDA, ROCm, etc).
Your future colleagues will be similarly highly skilled, with experience across industry and the drive to innovate. You will find yourself in a low-management work environment that encourages teamwork and respect for individuals’ expertise. Benefits include private medical insurance, generous pension scheme and access to local social and sports clubs. Please note, you are required to be onsite full-time for this position.
Another top job from ECM, the high-tech recruitment experts.
Even if this job's not quite right, do contact us now - we may well have the ideal job for you. To discuss your requirements call (phone number removed) or email your CV. We will always ask before forwarding your CV.
Please apply (quoting ref: CV27413 ) only if you are eligible to live and work in the UK. By submitting your details you certify that the information you provide is accurate.
Machine Learning Engineer
Posted today
Job Viewed
Job Description
Who We Are
At Ultralytics , we relentlessly drive innovation in AI, building the world's leading open-source models . We're looking for passionate individuals obsessed with AI, eager to make a global impact, and ready to excel in a dynamic, high-energy environment. Join our team and help shape the future of Vision AI .
Location and Legalities
This full-time Machine Learning Engineer position is based onsite in our brand-new Ultralytics office in London, UK. Applicants must have legal authorization to work in the UK, as Ultralytics does not provide visa sponsorship.
Machine Learning Engineer
Posted today
Job Viewed
Job Description
Are you a Junior Machine Learning Engineer eager to turn messy, complex data into real-world intelligence?
We’re looking for a curious and motivated Junior ML Engineer to join a hybrid-working team building cutting-edge data intelligence tools for the financial sector. You’ll spend part of your time collaborating in person with engineers and data scientists, and part working remotely — giving you the best of both worlds.
You’ll be working on a platform that transforms unstructured private market data into actionable insights — learning how to design ML pipelines, fine-tune NLP models, and deploy solutions that really work in production.
In this role, you’ll help train, test, and optimise models that can read, understand, and structure complex documents at scale. From data preprocessing to model evaluation, you’ll gain hands-on experience across the machine learning lifecycle — while contributing to a product used by real-world clients.
What’s in it for you?
AI That Matters – Work on models that make sense of unstructured financial documents and turn them into structured insights.
Hands-On ML Experience – Learn the full ML workflow — from cleaning data to deploying models and monitoring them in production.
Mentorship & Growth – Work closely with experienced ML engineers who will guide your technical and career development.