1 to 25 of 140 Machine Learning Jobs in the Thames Valley

Title: Machine Learning Engineer (Computer Vision) Location: Oxford Salary: Up to £160,000 (DOE) We are looking for a Machine Learning Engineer with experience in Computer Vision to join a growing engineering team developing machine learning solutions for complex real-world environments. This role … engineers, data scientists, and domain experts. The Role You will be responsible for designing, training, and deploying computer vision models, working across the full machine learning lifecycle. The work will involve building production-ready systems, evaluating model performance, and contributing to technical decisions across a range of projects. ...

level. You’ll be a Lead Machine Learning Engineer. The role will combine technical leadership, delivery leadership and line management responsibility for ML engineers within Aioi R&D Lab. It will help shape ML engineering best practice, support solution design, mentor junior engineers, and lead multidisciplinary teams across … future, and share in our success, we’d love to hear from you. BE THE NEXT BIG THING, NOW. Responsibilities Line manage and develop ML engineers, providing coaching, mentoring, feedback and performance support; contributing to hiring, onboarding and capability development within the ML engineering function. Maintain a meaningful individual contribution ...

addressing the global challenges encapsulated in EIT’s Humane Endeavors. Your Role: At EIT we are seeking an experienced and detail orientated Bio‐ML Scientist to develop AI and machine learning systems that drive GBI’s scientific aims, working alongside researchers and technical staff to address key questions … multiple data modalities with a focus on biological system modelling and optimisation. This is an exceptional opportunity to join GBI’s Technology Hub on ML Engineering, a fast‐growing team at the forefront of AI/ML and synthetic biology with access to exceptional facilities and expertise. We are looking ...

defining best practices. Working with clients, and cross-functional teams, you’ll ensure technical feasibility and timely delivery of high-quality, production-grade ML systems. What you’ll be doing: Building and deploying production-grade ML software, tools, and infrastructure. Creating reusable, scalable solutions that accelerate the delivery of ML … implementing Faculty’s standards for deploying machine learning at scale. Acting as a technical advisor to customers and partners, translating complex ML concepts for stakeholders. Who we’re looking for: You understand the full machine learning lifecycle and have experience operationalising models built with frameworks like ...

support of the CODAS project and related R&D Lab initiatives. Contribute to the delivery of technical components for a sovereign AI ecosystem, including ML services, data processing pipelines, evaluation tooling and deployment‐ready applications. Support the translation of research outputs into robust, maintainable and operationally viable systems. Work with … internal colleagues and external project partners to understand technical requirements, constraints and delivery priorities. Help adapt AI and ML approaches to privacy‐sensitive, security‐conscious and regulated deployment contexts. Contribute to the integration of technical solutions into project infrastructure, workflows and partner environments. Troubleshoot technical, data and integration issues arising ...

complex challenges with cutting‐edge technologies. You will work with key client stakeholders to understand business requirements and design solution proposals. You will use machine learning algorithms and other tools to develop and execute data models. You will consult with key internal and external stakeholders to determine … meeting with client stakeholders to discuss their business requirements. Design and implement a data pipeline for processing large datasets. Develop and execute a machine learning model to solve a business problem. Present your findings and recommendations to a variety of audiences. Collaborate with other engineers and data scientists ...

interested in working on real world data like no other? Viridien is expanding its capabilities in agentic AI, large language models and reinforcement learning for complex scientific and enterprise workflows. We are looking for a hands-on Machine Learning Engineer to design, develop and evaluate intelligent agent … real world data. About the TeamLearn more about our work and the team on our website, recent blog post featuring one of our senior machine learning engineers and our latest Voices of Viridien. Key responsibilitiesDesign and develop single-agent and multi-agent systems for complex workflows. Build reasoning ...

looking for a talented Senior Algorithms Engineer to join an innovative engineering team developing advanced machine learning and computer vision solutions for complex, real-world applications. This is an exciting opportunity for an experienced engineer to work on challenging perception and intelligence problems, applying techniques across AI, computer … technically challenging projects, influence future development activities, and support the growth of engineering capability through collaboration and mentoring. Key Responsibilities Develop and optimise machine learning and computer vision algorithms for real-world applications. Investigate complex technical challenges, designing experiments and approaches to identify effective solutions. Analyse datasets, model ...

Project Work with Hugging Face to build a sentiment analysis classifier using real-world AI techniques. Step 8 – AI Prompt Engineering Master prompt engineering, learning how to craft effective prompts for controlling AI outputs. Step 9 – Retrieval-Augmented Generation (RAG) Learn how to integrate external knowledge into AI systems … Combine prompt engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine ...

Project Work with Hugging Face to build a sentiment analysis classifier using real-world AI techniques. Step 8 – AI Prompt Engineering Master prompt engineering, learning how to craft effective prompts for controlling AI outputs. Step 9 – Retrieval-Augmented Generation (RAG) Learn how to integrate external knowledge into AI systems … Combine prompt engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine ...

Project Work with Hugging Face to build a sentiment analysis classifier using real-world AI techniques. Step 8 – AI Prompt Engineering Master prompt engineering, learning how to craft effective prompts for controlling AI outputs. Step 9 – Retrieval-Augmented Generation (RAG) Learn how to integrate external knowledge into AI systems … Combine prompt engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine ...

support of the CODAS project and related R&D Lab initiatives. Contribute to the delivery of technical components for a sovereign AI ecosystem, including ML services, data processing pipelines, evaluation tooling and deployment‐ready applications. Support the translation of research outputs into robust, maintainable and operationally viable systems. Work with … internal colleagues and external project partners to understand technical requirements, constraints and delivery priorities. Help adapt AI and ML approaches to privacy‐sensitive, security‐conscious and regulated deployment contexts. Contribute to the integration of technical solutions into project infrastructure, workflows and partner environments. Troubleshoot technical, data and integration issues arising ...

What you'll do Own the technical direction of assigned CODAS research tracks, from framing the problem to validating the results. Design and build ML approaches for privacy-preserving generative AI, including differential privacy, federated learning, secure inference, and related techniques. Turn research into proof-of-concept systems … Publish, contributing to papers, technical reports, and conference talks that put the Lab's work in front of the wider AI community. Mentor other ML scientists and research associates working alongside you on the programme. Work directly with partner organisations to understand real technical constraints, not just theoretical ones. What ...

Worldwide Field Operations (WWFO) team is looking for a Solution Architect with expertise in Generative AI, Data Science applications and Machine Learning (ML) to work with our Hyperscaler partners. In our Solutions Architecture team, we work with the most exciting platform for accelerated computing and drive the latest … Electrical/Computer Engineering, Physics, Mathematics, other Engineering fields A proven track record of academic and/or industry experience in fields related to machine learning, deep learning and/or data science You are excited to work with multiple levels and teams across organizations (Engineering, Product ...

libraries. Excellent communication skills, with the ability to explain technical concepts clearly to geoscientists, software engineers, data scientists, and product stakeholders. AI/ML Implementation Design, implement, and test AI/ML methods that automate or enhance subsurface interpretation, prediction, and modelling. Apply data-driven approaches to sparse, noisy … geoscientists, software engineers, data scientists, and product teams to turn research ideas into practical prototype workflows. Stay current with relevant advances in AI/ML, geoscience analytics, and subsurface modelling, and assess how they can be applied within Landmark workflows. Lead and contribute to technical presentations, publications, patent disclosures ...

consideration and company funding. Your main responsibilities will be to Have an in-depth knowledge of the management, methods for development, methods for deployment, ML-Operations and procurement of AI solutions in multiple projects and/or solution elements, and specifically: Understanding and Management of Generative AI and associated technologies … that corporate AI capability is advanced. Support workshops, discovery activities and requirements gathering. Be adept with both Predictive Analytics environments as well as ML Classifiers. Develop solutions for, and in deploying on, public and private cloud technologies, particularly Azure or AWS. Manipulate, process, and extract value from large, disconnected datasets ...

looking to make a difference in silicon. What they're looking for: First degree in relevant STEM subject 3+ years in industry building production ML systems Python + PyTorch/JAX expertise for training, inference, and model export Experience building data pipelines for complex scientific/engineering datasets Solid software … engineering fundamentals - testing, CI/CD, clean APIs End‐to‐end ML system ownership from data ingestion to model deployment Clear communication - writing specs, documenting APIs, presenting to customers Familiarity with circuit simulation or EDA tools (nice to have) C++/CUDA experience for performance‐critical components (nice to have ...

traditional data annotation role. You'll be responsible for developing and improving annotation workflows, maintaining tooling, ensuring dataset quality, and working closely with machine learning engineers to create reliable training data for advanced computer vision models. You'll play a key role in ensuring data quality throughout … machine learning lifecycle, helping improve model accuracy by creating robust, well-structured datasets. Responsibilities Prepare, curate and annotate large-scale image and video datasets. Develop and improve annotation workflows and tooling. Configure and maintain annotation platforms. Create annotation guidelines and documentation. Validate dataset quality and consistency. Perform quality ...

traditional data annotation role. You'll be responsible for developing and improving annotation workflows, maintaining tooling, ensuring dataset quality, and working closely with machine learning engineers to create reliable training data for advanced computer vision models. You'll play a key role in ensuring data quality throughout … machine learning lifecycle, helping improve model accuracy by creating robust, well-structured datasets. Responsibilities Prepare, curate and annotate large-scale image and video datasets. Develop and improve annotation workflows and tooling. Configure and maintain annotation platforms. Create annotation guidelines and documentation. Validate dataset quality and consistency. Perform quality ...

traditional data annotation role. You'll be responsible for developing and improving annotation workflows, maintaining tooling, ensuring dataset quality, and working closely with machine learning engineers to create reliable training data for advanced computer vision models. You'll play a key role in ensuring data quality throughout … machine learning lifecycle, helping improve model accuracy by creating robust, well-structured datasets. Responsibilities Prepare, curate and annotate large-scale image and video datasets. Develop and improve annotation workflows and tooling. Configure and maintain annotation platforms. Create annotation guidelines and documentation. Validate dataset quality and consistency. Perform quality ...

safely and efficiently into production. This is a key operational, technical and leadership role at the intersection of science, software engineering, high-performance computing, machine learning and 24/7 operational delivery. You will provide technical and people leadership for the team responsible for ensuring that ECMWF … dissemination steps are aligned and robust. It oversees workflows used to produce operational weather forecasts from medium‐range to seasonal timescales, as well as machine‐learning‐enabled forecasts, Copernicus climate reanalyses and atmospheric composition services and Destination Earth Digital Twins. It also monitors the performance of operational suites ...

fully remote for the right person The role This is a genuine dual role: real line management and delivery leadership across the Lab's ML engineering function, plus a meaningful hands-on contribution to technical delivery yourself. You'll manage a growing team of ML Engineers and Scientists, shape ML … stay close enough to the work to actually lead it technically, not just report on it. What you'll do Line-manage and develop ML engineers: coaching, mentoring, feedback, and input into hiring and onboarding. Stay hands-on with technical delivery on selected projects, alongside your leadership responsibilities across multiple ...

Build reproducible model training, evaluation, and containerised deployment pipelines capable of operating in air-gapped or low-bandwidth environments. Technical Client Advisory: Translate complex ML/AI concepts into clear technical recommendations for MoD stakeholders, DSTL assessors, and Prime contractors. Required Qualifications & Experience Defence & AI Governance Active UK SC Clearance … minimum). Strong understanding of AI safety, non-repudiation, and human-in-the-loop operational constraints ( JSP 936 V1.1/Dependable AI ). ML & Edge Inference Mastery 3+ years of production experience deploying ML models to edge runtime environments (LiteRT/TFLite, ONNX, C++ bindings). Experience in model quantization ...

agent ecosystems encompassing multi-agent orchestration, tool use, skills use, and memory systems, as well as foundation model integration, fine-tuning strategies, and classical ML model deployment within cohesive, production-ready platforms. You will be accountable for ensuring the complete architecture meets the most rigorous non-functional requirements across security … strategy adaptation, fine-tuning, and dynamic cost/quality/latency-aware routing Set the standards for high-throughput, low-latency inferencing and classical ML deployment within unified, production-ready platforms Own the architecture of the enterprise context layer knowledge graphs, ontologies, vector search, and semantic retrieval grounding the solution ...

Data Science, based in any of our Brussels (Belgium), Slough (UK) or Raleigh (US).About the roleYou will help shape how advanced AI, machine learning, and computational methods support clinical development. You will design, validate, and deploy models that help teams make evidence-based decisions in areas such … guidance. You understand supervised, unsupervised, Bayesian, and deep learning methods, and can apply them to real-world scientific questions. You have experience with ML infrastructure, reproducible research, Linux or HPC environments, and software or platform development. You communicate clearly with scientific, technical, medical, and business partners, and enjoy working ...