Machine Learning Engineer Jobs in East Anglia

4 of 4 Machine Learning Engineer Jobs in East Anglia

Machine Learning Engineer

hertfordshire, east anglia, united kingdom
Hybrid / WFH Options
Rightmove
We are looking for a Machine Learning Engineer Location: London Reporting to: Head of AI The role We are looking for a talented Machine Learning Engineer who thrives in environments where reliability, scale, and impact truly matter. At Rightmove, you'll join a close-knit, collaborative AI team that's developing, shipping and operating … and value to consumers, our partners and all our stakeholders across the UK property market. You'll be at the heart of a greenfield opportunity - building, deploying, and operating machine learning systems that leverage Rightmove's data at large scale. You'll have the opportunity to shape best practices, own and grow the ML Ops discipline, and help … us move from first launches to robust, sustainable production. In this role, you will work in a cross-functional team to productionise machine learning and AI models, ensuring they are robust, scalable, and measurable. You'll collaborate closely with data scientists, engineers, and product teams to automate workflows, monitor performance, and retrain models as needed. You'll bring More ❯
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Senior Machine Learning Engineer

cambridge, east anglia, united kingdom
Hybrid / WFH Options
IC Resources
Senior Machine Learning Engineer Location: Cambridge (Hybrid) Salary: £60,000 – £70,000 + Share Options A growing AI company is developing intelligent imaging software that applies advanced machine learning to medical data, improving diagnostic accuracy and speed. As a Senior Machine Learning Engineer, you’ll design, train and deploy ML models for … Build and integrate AI pipelines within scalable production environments Collaborate with data, clinical and software teams to ensure robust, validated outputs Skills & Experience MSc/PhD in Computer Science, Machine Learning or related discipline 3+ years’ experience developing ML models, with a strong focus on medical imaging Proven track record using deep learning frameworks (PyTorch/TensorFlow More ❯
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Machine Learning Engineer

cambridge, east anglia, united kingdom
Hybrid / WFH Options
Neutreeno
for Sustainability Leadership for the 2025 Earthshot Prize, we're ready to grow. Join us in revolutionising decarbonisation and tapping into the $130B addressable market! The Role As a Machine Learning Engineer at Neutreeno, you'll lead the development of intelligent systems that power our emissions and decarbonisation capabilities. Working at the cutting edge of machine learning and sustainability, you'll build platforms that transform complex data into actionable insights for thousands of companies globally. Your innovations will directly power breakthrough solutions that identify critical decarbonisation opportunities across entire industries and supply chains. You'll push the boundaries of what's possible with AI-driven climate tech developing advanced models that process vast amounts … tune out-of-the-box models for matching textual and quantitative data to entries in our emissions database with uncertainty estimation Develop our emission intensity inference model using deep learning techniques that leverage uncertainty Advise on the out-of-the-box Large Language Models to extract data from a variety of sources Advise on construction of data-pipelines to More ❯
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Machine Learning Engineer

cambridge, east anglia, united kingdom
Harnham
Machine Learning Engineer We are working with a new start up company who are developing state-of-the-art medical devices to monitor health systems. Experience Required: MSc or PhD in ML, Biomedical Engineering, or related field Strong experience with PyTorch/TensorFlow and Python Hands-on experience with TinyML or edge ML frameworks (TFLite, TVM, etc. … Skilled in model optimization for constrained devices Comfortable in a startup environment - proactive, collaborative, and adaptable What you'll do: Build and optimize deep learning models for on-device biosignal monitoring Work on model compression, quantization, and other techniques for edge deployment Collaborate closely with the CTO and technical team to deploy models in production Contribute across the stack More ❯
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