376 to 400 of 2,850 Machine Learning Jobs in the UK

Machine Learning Engineer (Computer Vision) Department: Vicon Markerless Employment Type: Permanent - Full Time Location: Botley, Oxfordshire Reporting To: Timothy Smith Description Are you interested in working on products at the very cutting edge of technology? Want to join Vicon, an Academy Award-winning company, and the world's largest supplier of precision motion capture and tracking systems? Vicon … vision problems - such as object detection and human pose estimation - with the application of appropriate machine learning methods, such as CNNs and ViTs, in conjunction with non-ML algorithms. • Demonstrated experience using leading-edge methods for modelling human and object shape, appearance and movement. • Excellent team working abilities with positive, can-do attitude. • Examples of working with large … spatio-temporal datasets. • Experience with Python and ML toolkits, e.g. PyTorch, Lightning, etc. Desirable Skills • Relevant conference, journal, or other peer-reviewed output. • Experience delivering the full ML development lifecycle, taking systems from research prototypes through to development and production within a standalone application. • Experience with model quantisation and optimisation for deployment, e.g. on GPUs. • Experience, aptitude, and a desire More ❯

Machine learning. A long way has come since Sci-Fi films like Terminator and iRobot got us thinking about robots taking over the world. But in the 2020s, hearing AI and machines in the same sentence means a world of innovation. This is a chance to be part of a brand new Machine Learning team within one … tools for model training and evaluation, collaborating with Data Scientists and Engineers to get these solutions into production, and driving improvements in MLOps processes. Youll have worked as a Machine Learning Engineer or Data Scientist in the past, ideally centred around a software product, and have solid Python coding skills, and expertise with cloud infrastructure (preferably AWS). … tools such as MLflow and Airflow is essential, with any knowledge of AI SaaS or GenAI APIs being is a bonus. But what truly matters is your passion for learning and advancing technology. In return, youll be offered a supportive team culture with flexible, hybrid work options and room for professional growth. If you're eager to contribute to More ❯

brand values in everything you do. A collaborative, pragmatic approach to working in cross-functional Agile squads. Your experience: Expert-level fluency in Python (required) with deep experience in ML, OR, and DS libraries (e.g. scikit-learn, pandas, numpy, Gurobi). Strong knowledge of machine learning and optimisation techniques-including supervised, unsupervised learning, and operations research methods. … assess trade-offs, and select effective modelling approaches. Excellent communication skills and the ability to influence both technical and non-technical stakeholders. A track record of delivering production-grade ML/optimisation solutions that create tangible business impact. Qualifications: Master's degree or above in Data Science, Machine Learning, Operational Research or a related field, or 6+ years … of highly relevant industry experience (required). 4-6 years working on production ML or optimisation software products at scale (required). Experience developing industrialised data science software products (required). Domain knowledge in transport, operations, or network optimisation (preferred). Are you ready to lead the future of data-powered decision-making at the heart of aviation? Apply now More ❯

Engineer, you will be responsible for designing, deploying, and maintaining scalable infrastructure and processes that support our AI systems in production. Your time will be divided between improving our ML infrastructure, building deployment and monitoring systems, and working closely with our ML engineers and product teams. This is an excellent opportunity for those with strong Engineering and DevOps capabilities and … in operationalising AI solutions. We are looking for someone with complementary skills that extend into infrastructure and observability, preferably with experience in E-Commerce. The AI team owns all ML-related research, implementation and maintenance. In practice, this means keeping up to date with best practices in production ML, developing and supporting scalable infrastructure, and enabling faster and safer experimentation … and deployment. Responsibilities Proactive approach with team members and clients Continuous improvement of ML infrastructure and operations Take ownership of the deployment and monitoring pipelines within your expertise Contribute to the ongoing innovation R&D projects by enabling production readiness Maintain and implement CI/CD pipelines, observability, and infrastructure for ML services Requirements Degree in relevant field with 3+ More ❯

for internal engineering teams. Microservices & API Gateways Guide distributed system architectures and internal service integration . Define best practices for service-to-service communication and data management . AI & ML Enablement Set vision for MLOps platforms and streamline machine learning workflows . Enable deployment of traditional and generative AI models into internal platforms. Developer Experience & DevOps Tooling Shape … as Code (IaC) , and monitoring frameworks . Enhance developer productivity , deployment velocity , and system reliability . Key Responsibilities Define and maintain product roadmaps for platform , infrastructure , and AI/ML tooling . Act as primary product partner to engineering, SRE, and data science teams. Lead initiatives that boost developer experience , system observability , and engineering efficiency . Foster a culture of … SRE teams on internal tooling and shared services. Track record of delivering internal products that boost developer workflows , reliability , or deployment velocity . Hands-on experience with AI/ML platforms , MLOps , and deploying machine learning models into production environments. Core Focus Areas Core Platform Engineering Developer Experience (DevEx/DX) Engineering Productivity DevOps Tooling Observability Solutions Platform More ❯

for internal engineering teams. Microservices & API Gateways Guide distributed system architectures and internal service integration . Define best practices for service-to-service communication and data management . AI & ML Enablement Set vision for MLOps platforms and streamline machine learning workflows . Enable deployment of traditional and generative AI models into internal platforms. Developer Experience & DevOps Tooling Shape … as Code (IaC) , and monitoring frameworks . Enhance developer productivity , deployment velocity , and system reliability . Key Responsibilities Define and maintain product roadmaps for platform , infrastructure , and AI/ML tooling . Act as primary product partner to engineering, SRE, and data science teams. Lead initiatives that boost developer experience , system observability , and engineering efficiency . Foster a culture of … SRE teams on internal tooling and shared services. Track record of delivering internal products that boost developer workflows , reliability , or deployment velocity . Hands-on experience with AI/ML platforms , MLOps , and deploying machine learning models into production environments. Core Focus Areas Core Platform Engineering Developer Experience (DevEx/DX) Engineering Productivity DevOps Tooling Observability Solutions Platform More ❯

What You'll Be Doing Automating Machine Learning workflows (training deployment) with AWS & GitOps Deploying LLMs using Kubernetes & Docker Building infrastructure with Terraform & Helm Monitoring and maintaining ML models with performance alerts and dashboards Supporting CI/CD for ML pipelines Developing production-grade APIs (REST/gRPC) to serve models Collaborating with engineers, data scientists & DevOps teams … Your Experience Industry experience in DevOps or MLOps roles (ideally in AWS environments) Hands-on with Docker, Kubernetes, and Terraform Strong scripting skills in Python or Bash Familiar with ML lifecycle tools, model monitoring, and versioning Exposure to tools like KServe, Ray Serve, Triton, or vLLM is a big plus Bonus Points Experience with observability frameworks like Prometheus or OpenTelemetry … Knowledge of ML libraries: TensorFlow, PyTorch, HuggingFace Exposure to Azure or GCP Passion for financial services Qualifications Degree in Computer Science, Engineering, Data Science, or similar What We Offer A collaborative and innovative work environment with excellent career growth opportunities 34 days holiday plus your birthday off (including bank holidays) Share options - we believe in shared success Skills development - continuous More ❯

enabling technologies; and developed the fundamental theories of these technologies. We invite you to join us on this exciting journey and drive your career forward. Job Summary The Reinforcement Learning Team at the Huawei London Research Centre is seeking a highly skilled and research-driven Machine Learning Scientist to join our team. Our group combines world-class … Specification: Required: PhD (or equivalent research experience) in Computer Science, Machine Learning, Artificial Intelligence, or a related field. Strong research track record with publications at top-tier ML/AI venues: ICML, ICLR, JMLR, NeuRIPS and the like. Deep expertise in at least two of the following: reinforcement learning, Bayesian optimisation, AI agents, LLMs, VLMs. Proficiency in … Python and experience with at least one major ML framework (PyTorch, TensorFlow, or JAX). Ability to work in a fast-paced, research-oriented environment with ambiguous and evolving goals. Excellent problem-solving, collaboration, and communication skills. Ability to lead a team of junior researchers and engineers. Passion for bridging fundamental AI research with impactful applications. What we offer More ❯

innovation across STEM sectors, helping them to Outpace tomorrow, together. What are the key expectations of this role? Design and develop AI models and solutions using Azure OpenAI, Azure Machine Learning, and Azure Cognitive Services to address specific business challenges. Implement and maintain scalable and efficient AI systems, ensuring they meet business requirements and performance benchmarks. Collaborate with … business analysts, data scientists, and IT teams to integrate AI solutions into existing systems and workflows, enhancing their capabilities and impact. Stay abreast of advancements in AI, machine learning, and Azure services, incorporating new technologies and methodologies to continually improve solution offerings. Provide expertise and guidance on AI best practices, contributing to the organization's AI strategy and … such as Python, C#, or Java, with a deep understanding of software development principles. Extensive experience with Azure AI solutions, including Azure OpenAI Service, Azure Cognitive Services, and Azure Machine Learning. Familiarity with Azure Databricks is a plus. Solid background in machine learning algorithms, data pre-processing, feature engineering, and model evaluation. Experience with deep learning More ❯

Machine Learning Engineer with deep technical expertise and a passion for applying AI to real-world biological problems.?? What You’ll Be Working On: Designing and deploying ML models for protein structure prediction , genomic pattern recognition , and cell image segmentation Collaborating with bioinformaticians, data scientists, and software engineers to build scalable pipelines for research and clinical applications Fine … tuning and optimizing models using tools like AlphaFold , RoseTTAFold , BioBERT , and DeepCell Integrating ML workflows with platforms such as Benchling , PubMed APIs , and internal R&D systems Supporting model validation, performance benchmarking, and regulatory documentation Key Technologies & Tools: ML Frameworks: PyTorch, TensorFlow, Hugging Face Transformers Bio-AI Tools: AlphaFold, RoseTTAFold, BioBERT, DeepCell, Cellpose Data Sources: Genomic datasets, microscopy images, biomedical … Strong understanding of biological data types (e.g., DNA/RNA sequences, protein structures, cell images) Experience working with open-source bioinformatics tools and APIs Comfortable building end-to-end ML pipelines in cloud environments Familiarity with regulatory considerations in clinical or research settings (e.g., HIPAA, GxP More ❯

Machine Learning Engineer - Search and Recommendation JD.com (NASDAQ: JD and HKEX: 9618), also known as JINGDONG, has evolved from a pioneering e-commerce platform into a leading technology and service provider with supply chain at its core. Renowned for its supply chain innovation and excellence, the company has expanded into sectors including retail, technology, logistics, healthcare, and more … aiming to transform traditional business models with cutting-edge digital solutions. Know more about us: We have an exciting opportunity for a Machine Learning Engineer to join our growing technical team at Joybuy ( ). Joybuy is JD.coms European full-category online retail brand designed to bring customers a faster, more convenient, and cost-effective shopping experience. Offering same More ❯

requirements. Architecting end-to-end solutions encompassing data modelling, ingestion, transformation, visualization, and predictive modelling. Designing and implementing data pipelines and integrations for diverse data sources. Developing and deploying machine learning models using OML, Oracle Data Science, and other tools. Client & Business Engagement : Collaborating with stakeholders to understand analytical needs and translate them into technical specifications. Building and … clients Bachelor's or Master's degree or equivalent in a related field. Proficiency in SQL, PL/SQL, and other data manipulation languages. Hands-on experience with Oracle Machine Learning (OML) or other machine learning libraries. Knowledge of cloud computing platforms, preferably Oracle Cloud Infrastructure (OCI). Excellent communication, presentation, and interpersonal skills. Strong analytical More ❯

voice model training and an intuitive sense for optimisation. Exceptional communication and teamwork skills to thrive in a collaborative environment. Nice to Have Prior experience collaborating with AI or machine learning teams. Basic scripting skills or experience with Python and machine learning tools. Interest in machine learning workflows and voice model training. About You More ❯

join our Product Listings team-focused on unlocking smarter, more scalable advertising through automation and optimisation. This is a hybrid role combining deep data science expertise with production-grade ML engineering. You'll be a driving force behind our performance marketing automation: designing experiments, building predictive models, and deploying them at scale to help optimise product bidding and maximise profit … across platforms like Google Shopping. Expect to work across the full ML lifecycle-from exploring large, messy datasets and engineering features, to evaluating models offline and running experiments to validate impact. At the same time, you'll build, deploy and monitor models in production: setting up retraining workflows, pipeline orchestration, and performance alerts. You will be supported in this by … your tech lead and colleagues from the wider Data Science chapter at Lyst. We work mainly in Python using all the standard ML toolkits and frameworks (e.g. SKLearn, Tensorflow, Pytorch), and run our ML code in the AWS environment using Sagemaker where possible. We have a strong preference for clean, documented, well tested and reviewed code and have tooling and More ❯

days/week in office) Up to £110k Shares Benefits A fast-growing Data & AI company at the forefront of cutting-edge AI solutions are looking for an ML Lead to join the team and spearhead a number of ambitious projects, shaping the architecture, direction, and delivery of advanced AI initiatives. What you’ll do Lead the design and development … of Agentic AI systems, generative models, and NLP-powered solutions. Guide and manage a small talented ML engineering team, fostering innovation and technical excellence. Collaborate with product, data science, and engineering teams to bring state-of-the-art research into production. Evaluate and implement the latest AI frameworks, libraries, and cloud tools. Champion best practices in model deployment, evaluation, and … optimisation. What we’re looking for Strong track record in ML leadership, ideally in production-scale AI systems. Expertise in Agentic AI, LLM-based architectures, NLP techniques, and generative AI models. Solid programming skills (Python preferred) and experience with ML frameworks such as PyTorch, TensorFlow, Hugging Face. Hands-on experience with prompt engineering, fine-tuning LLMs, and building multi-agent More ❯

connect data, software, and purpose to create extraordinary outcomes. You could say we are a digital transformation business. We specialize in software product development, analytics, data science, IoT solutions, machine learning, DevOps optimization, and modernization of applications, data, and platforms. We work with incredible clients in all types of industries such as smart home devices, space exploration, beer … connect data, software, and purpose to create extraordinary outcomes. You could say we are a digital transformation business. We specialize in software product development, analytics, data science, IoT solutions, machine learning, DevOps optimization, and modernization of applications, data, and platforms. We work with incredible clients in all types of industries such as smart home devices, space exploration, beer … . Strong Pluses Degree in Computer Science or similar technical discipline (helpful, not required). Hands-on experience with Azure cloud services or Power BI. Exposure to AI/machine-learning/GenAI product development. Experience with Azure DevOps, JIRA, Confluence, or similar tools. Why Join Us At Ascent, we help clients connect data, software, and purpose to More ❯

/Contract options available Start Date: Flexible About the Role We're hiring a remote AI Engineer with strong Python skills to help build intelligent systems across domains like machine learning , natural language processing , and generative AI . You'll be part of a collaborative team working on real-world applications, from prototyping to production deployment. This is … on role ideal for someone who enjoys solving complex problems, writing clean code, and staying at the forefront of AI innovation. Key Responsibilities Design and implement scalable AI/ML pipelines using Python Build, fine-tune, and deploy machine learning models (including LLMs and transformers) Develop APIs and backend services to integrate AI models into applications Collaborate on … research and tools, and apply them to real-world use cases Contribute to code reviews, testing, and documentation Required Skills & Experience Strong proficiency in Python and its AI/ML ecosystem (e.g., NumPy, Pandas, Scikit-learn, PyTorch, TensorFlow) Experience with machine learning model development , training, and deployment Familiarity with LLMs , NLP , or computer vision techniques Solid understanding of More ❯

chatbots and virtual assistants using conversational AI techniques. Present findings and recommendations to stakeholders, including technical and non-technical audiences. Research and stay updated on the latest AI and machine learning technology advancements. Collaborate with others to monitor the performance of deployed AI tools, identify areas for improvement, and perform regular maintenance to ensure stability and accuracy. Collaborate … organizational goals. You Have Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, Engineering, or a related technical field. 1 - 2 years of experience working with AI/ML concepts and technologies (e.g., natural language processing, machine learning algorithms). Experience designing and deploying AI solutions, preferably within Salesforce environments, specifically automating tasks, enhancing knowledge systems, and … optimizing workflows for sales, service, billing, or professional services teams. Experience with cloud-based AI services (e.g., AWS AI/ML, Google Cloud AI, Azure AI). Understanding of software sales, support operations, and common customer service challenges. Strong analytical and problem-solving skills with a keen eye for detail. Excellent communication and collaboration skills, with the ability to translate More ❯

If you're passionate about operationalizing advanced machine learning-including large language models (LLMs) and generative AI-this is the place for you. As a Mid-Level ML Engineer within the International Consumer Bank at JPMorgan Chase, you'll work alongside ML scientists, Data Engineers and software engineers to build, deploy, and maintain sophisticated machine learning solutions in production. You'll play a hands-on role in implementing ML pipelines, deploying models (including LLMs), and developing the supporting infrastructure that keeps our AI-driven products robust and scalable. Job Responsibilities: Build, automate, and maintain ML pipelines for deploying advanced models, including large language models (LLMs), at scale. Collaborate with data engineers, scientists and product owners … seamless model deployment and monitoring. Implement monitoring, logging, and alerting for AI services, ensuring performance, security, and compliance in production environments. Write clean, maintainable, and efficient Python code for ML tooling, orchestration, and infrastructure. Develop and maintain infrastructure as code (IaC) using tools such as Terraform or CloudFormation. Work with containerization and orchestration technologies (e.g., Docker, Kubernetes) to support scalable More ❯

pragmatism, we aim to support the next generation of advanced materials critical to building a more sustainable future. You'll be joining our team of nine as a senior ML engineer. This role grants you a significant degree of autonomy, and influence over the development and direction of the platform and product. We're building a SaaS product that will … Engineering, AI, Math, Physics, or similar - or equivalent work experience (PhD in STEM subject desirable) 2+ years experience writing production-level code for computer vision based applications with Python ML libraries, e.g Pytorch, TensorFlow Proficiency with version control and cloud computing e.g. AWS, Azure Enthusiasm for complex problem solving Strong technical communication skills, including the ability to clearly disseminate new … ideas and ML concepts to the rest of the team Technologies We Use Machine Learning: Python/PyTorch CI/CD: Github, Github Actions. Frontend/Backend: TypeScript with React/Next.js and Express/Prisma. Infrastructure: Docker, Kubernetes, Terraform (AWS). Database: PostgreSQL. Salary £85,000-130,000 depending on experience. Even if you don't have More ❯

needed to deliver them to users with confidence. Key Impact Areas Build automated workflows for model training, evaluation, deployment, and monitoring. Establish best practices for CI/CD in machine learning, including model testing and version control. Monitor and track model behaviour in production … detecting drift and ensuring data quality. Partner with Data Scientists to containerise and operationalise models, including those with advanced retrieval or graph-based components. Configure and optimise cloud-based ML infrastructure (AWS, GCP, or Azure) for performance and scalability. Apply Infrastructure as Code (Terraform, Pulumi, etc.) to provision and manage environments. Integrate AI services into broader application architectures, working closely … with product and engineering. Drive continuous improvement across the ML lifecycle, from A/B testing to incident response. What Youll Bring 3+ years in MLOps, DevOps, or software engineering focused on ML systems. Familiarity with LLM deployment and operational support. Experience with Docker, Kubernetes, and cloud ML services. Understanding of vector databases and search optimisation strategies. Hands-on knowledge More ❯

What if you could use machine learning to predict human behaviour, not in theory, but in commercially critical decisions that shape what people buy Building the next generation of decision intelligence software, leveraging large scale simulations and behavioural modelling to help global companies … understand how customers respond to pricing, product mixes, and promotions. As a Senior Machine Learning Engineer, you'll play a pivotal role in designing and scaling the ML systems that power this transformation.You'll work closely with Data Scientists, Engineers, and Product teams to build robust, production grade models that deliver real time insights through a modern SaaS … that demand both depth and pragmatism. We're looking for someone with strong Python skills, experience with cloud based data processing, and a track record of delivering reliable, scalable ML systems. Familiarity with tools like PyTorch, scikit-learn, and modern ETL workflows is key. If you've worked in pricing, RGM, or simulation heavy domains, even better. Flexible hybrid setup More ❯

a minimum of 1 day per week. Our Data Environment Our Data teams are aligned to divisions covering the following Banking Services & Products, Customer Identity & Financial Crime and Data & ML Engineering. Our Data teams are excited about delivering meaningful and impactful insights to both the business and more importantly our customers. Hear from the team in our latest blogs or … for which they are responsible. Stakeholder Communication & Visibility: Ensure clear communication and good visibility with stakeholders such as risk teams, regarding how data scientists at Starling observe and manage ML and AI models. Observability Centre of Excellence: Support colleagues in enhancing their observability work by maintaining existing observability tooling, assisting in identifying key metrics to monitor, and providing expert advice … on internally-developed model behaviour characterisation techniques. Innovate and Implement Novel Methods: Develop and implement cutting-edge techniques and frameworks to deepen our understanding of AI and ML model behaviour, enabling the safe and effective exploitation of advanced AI. This includes contributing to initiatives such as LLM-as-a-judge, RAG evaluations, and agentic workflow assessment. To thrive in this More ❯

Machine Learning solutions for autonomous driving. Our team tackles groundbreaking challenges in designing state-of-the-art neural networks, pioneering innovative end-to-end architectures, and advancing ML techniques in perception, prediction, and motion planning. We're passionate about pushing the boundaries of autonomous systems through deep learning and optimization, particularly in complex 3D geometric computer vision … cross-org collaborative project is synergistic with TRI's robotics division's efforts in Diffusion Policy and Large Behavior Models (LBM). Responsibilities Support the design and development of ML models or model components for end-to-end autonomous driving: ranging from initial data strategy, design, development, experimentation, evaluation, and deployment; Able to navigate ambiguities and address uncertainties arising from … time zones to define interfaces and requirements for an end-to-end stack; Experience MS, or higher degree, in a related field, or equivalent industry experience Professional experience with ML frameworks such as PyTorch, Jax or Tensorflow (PyTorch preferred) Experience with data sampling and data curation pipelines for autonomous driving datasets Experience in state-of-the-art architectures for end More ❯

Machine Learning solutions for autonomous driving. Our team tackles groundbreaking challenges in designing state-of-the-art neural networks, pioneering innovative end-to-end architectures, and advancing ML techniques in perception, prediction, and motion planning. We're passionate about pushing the boundaries of autonomous systems through deep learning and optimization, particularly in complex 3D geometric computer vision … stack. This cross-org collaborative project is synergistic with TRIs robotics divisions efforts in Diffusion Policy and Large Behavior Models (LBM). Responsibilities Support the design and development of ML models or model components for end-to-end autonomous driving: ranging from initial data strategy, design, development, experimentation, evaluation, and deployment; Able to navigate ambiguities and address uncertainties arising from … time zones to define interfaces and requirements for an end-to-end stack; Experience MS, or higher degree, in a related field, or equivalent industry experience Professional experience with ML frameworks such as PyTorch, Jax or Tensorflow (PyTorch preferred) Experience with data sampling and data curation pipelines for autonomous driving datasets Experience in state-of-the-art architectures for end More ❯