51 to 55 of 55 Machine Learning Engineer Jobs in the UK

Core Duties Design and develop machine learning models for traditional ML use cases (forecasting, classification, anomaly detection) and GenAI/LLM applications Lead experimentation cycles: define hypotheses, design experiments, evaluate results, and iterate rapidly while adhering to governance requirements Transition validated experiments into production-ready solutions, working closely ...

Data/Machine Learning Ops Engineer Location: Erskine, Scotland (Hybrid 2/3 days per week in the office) Do you have the following skills, experience and drive to succeed in this role Find out below. Candidates must be eligible for clearance. DXC Technology (NYSE ...

Cambridge, MIT, Imperial, BBC R&D to name a few. We work a lot and are all close friends – come join the family! ML Engineer @ Matta We’re looking for an ML Engineer to join us in creating a brand-new class of foundation models designed specifically … collaborate with an exceptional team of top engineers, scientists, and builders, all obsessed with embodied AI reshaping the manufacturing world. About you A machine learning mage: You write clean, scalable, high-performance deep learning code. You take pride in your craft. Proficiency in PyTorch, Tensorflow ...

part of the product roadmap — with significant potential to unlock deeper data intelligence than traditional video-based systems — and we’re looking for an engineer to take ownership of this space end-to-end. Why Join Work on a greenfield product at an early stage Own a core product … across embedded, cloud, and ML teams High autonomy in a low-ego, high-performance environment Competitive salary + equity Strong long-term growth and learning opportunities The Role You’ll take full ownership of the audio subsystem, spanning real-time embedded processing through to cloud-based audio pipelines ...

Core Duties Design and develop machine learning models for traditional ML use cases (forecasting, classification, anomaly detection) and GenAI/LLM applications Lead experimentation cycles: define hypotheses, design experiments, evaluate results, and iterate rapidly while adhering to governance requirements Transition validated experiments into production-ready solutions, working closely ...