1 to 25 of 357 Remote/Hybrid Machine Learning Jobs in the UK excluding London

title: Senior Machine Learning Research Engineer Salary: £64,490 - £86,255 Location: Cambridge - Triangle/Hybrid (2 days per week in the office) Contract: Permanent Hours: Full Time (35 hours per week) Shape the future of AI-powered learning solutions with Cambridge University Press & Assessment, a world … solutions in production environments. Strong track record of successfully translating academic research into real-world applications and products. Ability to estimate suitability of candidate ML, NLP, LLM, and GenAI technologies for specific scenarios, estimate the time, cost and outcomes of different solutions, and apply effective risk management to ensure prompt ...

Machine Learning Operations Engineer Our financial services client based in London is looking to recruit a Machine Learning Operations Engineer ASAP. The position will be a Hybrid role be working from home and their offices in London. To be considered for the role you must have … within the company. Technical Skills required Previous experience in designing, building, optimising, deploying and managing business-critical machine learning models using Azure ML in Production environments. Experience in data wrangling using Python, SQL and ADF. Experience in CI/CD and DevOps/MLOps and version control. Familiarity ...

reliability, and performance Partner closely with data scientists to turn experimental models into well-engineered, production-ready systems Develop and maintain end-to-end ML pipelines, including feature engineering, training, evaluation, versioning, monitoring, and automated retraining Contribute to MLOps capabilities, including CI/CD pipelines, model registries, infrastructure automation … fairness analysis, and performance optimisation Collaborate with data engineers and architects to enhance data quality, data flows, and platform capabilities Lead experimentation using modern ML frameworks to assess new algorithms and technologies and make recommendations on adoption Support model governance processes, ensuring compliance with internal standards, documentation, transparency, and regulatory ...

model capability. THE ROLE As a Staff Machine Learning Engineer you will... Lead the design, development, and deployment of end-to-end ML solutions. Architect scalable ML systems and pipelines that integrate seamlessly with cloud infrastructure. Mentor engineers, championing best practices across coding, experimentation, and MLOps. Collaborate with … Product and Engineering teams to define priorities and model strategy. Apply deep learning, NLP or classical ML techniques to real-world, high-impact problems. Uphold responsible AI principles across model development and evaluation. YOUR SKILLS & EXPERIENCE The successful Staff Machine Learning Engineer will have: Strong Python skills ...

same! Key Responsibilities: Build, maintain, and productionise machine learning models using PyTorch or similar frameworks. Design and optimise data pipelines for ML inference at scale. Work with large datasets using Big Data tools. Deploy ML workflows using AWS infrastructure . Collaborate with data engineers and product teams … integrate ML solutions into RealityMine’s products. Investigate and troubleshoot customer feedback on data quality and drive model improvements from experimentation . Promote best practices in ML engineering and data quality across the business. Adhere to Company Policies and Procedures with respect to Security, Quality and Health & Safety. AI first ...

Role : Machine Learning Infrastructure Developer Location: Cambridge, UK (Hybrid ) Duration: 12 Months Responsibilities: Create robust, flexible, and scalable machine learning tooling and infrastructure that supports research scientists in leveraging large-scale internal infrastructure (e.g., source control, distributed compute clusters, data storage). Work collaboratively as part … signal processing experience . Experience collaborating closely with research users or internal customers to deliver robust, stable, and scalable tooling. Experience writing scalable ML pipelines or tooling used by research teams. Familiarity with Linux or Windows shell scripting. ...

Junior ML Operations Engineer (Python) Salary: Up to £40,000 depending on experience Location: Manchester - (Hybrid working - currently 40% on site increasing to 60% within 12 months) Ref: J13059 This is an exciting opportunity to build a career in production machine learning within a large scale pricing … will be supported by experienced engineers, exposed to modern tooling, and given the space to build confidence in production machine learning and ML Operations. This role is designed to set strong foundations for long term technical growth. Right to work You must be eligible and authorised to work ...

with a UK-based advanced technology organisation expanding its machine learning capability. The team works on non-trivial, real-world problems where ML is applied in technically challenging environments rather than consumer-facing products. This role sits between research and engineering, focusing on taking ML concepts and adapting … with engineers and researchers across disciplines What We’re Looking For Strong foundations in machine learning Hands-on Python experience with modern ML frameworks Comfortable working on open-ended technical problems Strong STEM background (degree or equivalent experience) Security Clearance Candidates must be eligible for UK Security Clearance ...

is delivered at scale within a modern data environment. Working on a strategic Lakehouse platform built on Databricks, you will influence how production ML models are designed, governed and optimised, helping the business turn complex data into reliable, decision-driving insight. The role combines hands-on engineering with MLOps … governance, access control, monitoring and retraining strategies * Develop automated model validation tests covering unit, integration, regression and bias checks * Translate business problems into effective ML solutions, managing ethical, privacy and data governance considerations * Establish model performance KPIs, reliability measures and production monitoring frameworks * Document model design, assumptions, metrics, risks ...

data and AI Required Skills: Experience in data science, machine learning, or applied analytics Strong proficiency in Python and common ML libraries (pandas, NumPy, scikit‐learn, TensorFlow, PyTorch) Experience designing, training, and evaluating machine‐learning models Solid understanding of statistical methods, predictive modelling, and experimental design … technical stakeholders Experience working in an agile delivery environment Strong problem‐solving skills and attention to detail Desired Skills: Experience with cloud‐based ML services (AWS SageMaker, Azure ML, Databricks) Familiarity with MLOps practices and model lifecycle management Experience with NLP, deep learning, or computer vision Knowledge of data ...

Data Annotator Analyst – AI/Machine Learning – Expedia Group Location: London (hybrid working) Duration: End of 2026 Pay: £223.18/day About the Role We are looking for a Data Annotator/Data Analyst to support the development and evaluation of AI and machine learning solutions. … consistent, and accurate annotations following defined guidelines Analyze annotated data to identify patterns, issues, and opportunities for improvement Work closely with data scientists and ML engineers to refine annotation strategies Use annotation tools (e.g., Label Studio or similar) to manage and review datasets Perform basic data processing and validation using ...

delivering advanced language and AI solutions to clients. The Role Lead and architect large-scale machine learning projects Build and deploy scalable ML models, pipelines, and systems Mentor engineers and set technical direction across teams Drive innovation through research and adoption of new ML techniques Present technical insights … Machine Learning Engineering or similar senior roles Strong Python skills; experience with deep learning frameworks (TensorFlow, PyTorch) Solid understanding of ML algorithms, statistics, and data modelling Experience with large-scale data tools (Hadoop, Spark, Kafka) Cloud & MLOps experience (AWS, Azure, or GCP) NLP experience highly beneficial Strong ...

Intelligence/Machine Learning applied to cyber security . This is a research-led role , focused on the security of AI/ML systems , exploring emerging threats, developing novel approaches, and shaping future cyber capability. You will work in an environment where problems are genuinely complex and often … have no off-the-shelf solutions . What You'll Be Doing Conducting hands-on AI/ML research in cyber security, with particular focus on the security of AI/ML systems Designing and prototyping innovative solutions to emerging cyber threats Translating research into practical outputs , including prototypes, reports ...

successfully transition into robust, enterprise-grade systems within a modern, cloud-native environment. Responsibilities: Contribute to the evolution of our Data Science platform, defining ML Engineering best practices, tooling and architecture as our team and portfolio grow. Drive automation across the end-to-end data science lifecycle using CI/… infrastructure-as-code to support scalable production workflows. Collaborate across the full model development and deployment lifecycle, spanning traditional ML and generative AI solutions. Work closely with data engineers, software engineers and wider business teams to deliver impactful, production-ready ML services. Write clean, maintainable, high-quality Python code following ...

production environments Collaborate with cross-functional teams to translate business problems into technical solutions Stay up to date with the latest AI/ML research, tools, and best practices Required Skills & Qualifications Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Mathematics, or a related field … Strong programming skills in Python Understanding of machine learning fundamentals (supervised/unsupervised learning, model evaluation, overfitting, etc.) Experience with common ML libraries such as PyTorch, TensorFlow, scikit-learn , or similar Solid foundation in data structures, algorithms, and software engineering principles Strong problem-solving skills and attention ...

Role Our client is looking for a Machine Learning Engineer to join their Spacetime team. This is a hybrid role combining ML research and engineering, focused on solving some of the most complex temporospatial networking and resource management problems in the industry. Youll work at the cutting edge … driven networking and space systems, collaborating with engineers, researchers, and customers globally. Key Responsibilities Research and develop state-of-the-art ML algorithms for network orchestration Build and manage ML training infrastructure using Kubernetes and MLOps tools Develop and maintain documentation for new algorithms and systems Integrate AI/ML ...

Senior Machine Learning Engineer Location Manchester, United Kingdom (Hybrid working) Why Apply? This is an opportunity to shape how enterprise machine learning is delivered at scale within a modern data environment. Working on a strategic Lakehouse platform built on Databricks, you will influence how production ML models are designed, governed and optimised, helping the business turn complex data click apply for full job details ...

predictive insights during the action. As a Lead Machine Learning Engineer , you'll shape the technical strategy and delivery of production ML systems that transform raw sports data and live video into real-time insights and personalised experiences for millions of fans. What … technical lead for a critical ML domain (e.g., live sports insights and personalisation , real-time ranking, computer vision for multi-angle video, or streaming inference). Expect to influence roadmaps, architecture, and platform evolution-not just single models-while mentoring engineers and data scientists and raising the bar across teams. ...

predictive insights during the action. As a Lead Machine Learning Engineer , you'll shape the technical strategy and delivery of production ML systems that transform raw sports data and live video into real-time insights and personalised experiences for millions of fans. What … technical lead for a critical ML domain (e.g., live sports insights and personalisation , real-time ranking, computer vision for multi-angle video, or streaming inference). Expect to influence roadmaps, architecture, and platform evolution-not just single models-while mentoring engineers and data scientists and raising the bar across teams. ...

predictive insights during the action. As a Lead Machine Learning Engineer , you'll shape the technical strategy and delivery of production ML systems that transform raw sports data and live video into real-time insights and personalised experiences for millions of fans. What … technical lead for a critical ML domain (e.g., live sports insights and personalisation , real-time ranking, computer vision for multi-angle video, or streaming inference). Expect to influence roadmaps, architecture, and platform evolution-not just single models-while mentoring engineers and data scientists and raising the bar across teams. ...

predictive insights during the action. As a Lead Machine Learning Engineer , you'll shape the technical strategy and delivery of production ML systems that transform raw sports data and live video into real-time insights and personalised experiences for millions of fans. What … technical lead for a critical ML domain (e.g., live sports insights and personalisation , real-time ranking, computer vision for multi-angle video, or streaming inference). Expect to influence roadmaps, architecture, and platform evolution-not just single models-while mentoring engineers and data scientists and raising the bar across teams. ...

predictive insights during the action. As a Lead Machine Learning Engineer , you'll shape the technical strategy and delivery of production ML systems that transform raw sports data and live video into real-time insights and personalised experiences for millions of fans. What … technical lead for a critical ML domain (e.g., live sports insights and personalisation , real-time ranking, computer vision for multi-angle video, or streaming inference). Expect to influence roadmaps, architecture, and platform evolution-not just single models-while mentoring engineers and data scientists and raising the bar across teams. ...

predictive insights during the action. As a Lead Machine Learning Engineer , you'll shape the technical strategy and delivery of production ML systems that transform raw sports data and live video into real-time insights and personalised experiences for millions of fans. What … technical lead for a critical ML domain (e.g., live sports insights and personalisation , real-time ranking, computer vision for multi-angle video, or streaming inference). Expect to influence roadmaps, architecture, and platform evolution-not just single models-while mentoring engineers and data scientists and raising the bar across teams. ...

predictive insights during the action. As a Lead Machine Learning Engineer , you'll shape the technical strategy and delivery of production ML systems that transform raw sports data and live video into real-time insights and personalised experiences for millions of fans. What … technical lead for a critical ML domain (e.g., live sports insights and personalisation , real-time ranking, computer vision for multi-angle video, or streaming inference). Expect to influence roadmaps, architecture, and platform evolution-not just single models-while mentoring engineers and data scientists and raising the bar across teams. ...

predictive insights during the action. As a Lead Machine Learning Engineer , you'll shape the technical strategy and delivery of production ML systems that transform raw sports data and live video into real-time insights and personalised experiences for millions of fans. What … technical lead for a critical ML domain (e.g., live sports insights and personalisation , real-time ranking, computer vision for multi-angle video, or streaming inference). Expect to influence roadmaps, architecture, and platform evolution-not just single models-while mentoring engineers and data scientists and raising the bar across teams. ...