201 to 225 of 965 Machine Learning Jobs in the UK excluding London

Head of AI Engineering will lead the design, deployment, integration and continuous improvement of enterprise AI and machine learning capabilities, including ML platforms, generative AI, LLM services, feature pipelines andMLOpstooling. The roleis responsible forestablishingAI engineering standards,governanceand best practices across the model lifecycle, ensuring solutions are scalable, secure … fast-paced technology environment. Strongexpertisein machine learning,MLOps, generative AI, LLMs, AI platforms and cloud technologies (e.g. Microsoft Azure AI/Azure ML). Proven experience implementing AI engineering standards, deployment automation, modelmonitoringand Responsible AI frameworks. Excellent analytical, problem-solving and stakeholder management skills. Strong written, verbal ...

Title: Deep Learning Researcher Location: London or Cambridge, UK Type: Permanent Our client are an international semiconductor company. Responsibilities: Lead engineering efforts on complex research projects in machine learning and artificial intelligence Optimize algorithms and ensure the scalability and robustness of research prototypes and systems Coordinate closely … related fields Requirements: PhD in Computer Science or related subject Publications in conferences such as: NeurIPS, ICLR, ICML, EMNLP, AAAI, IJCAI Extensive experience researching machine learning algorithms and systems Advanced proficiency in programming languages such as Python, C++, or similar Experience with optimization, reinforcement learning, and/ ...

Processing Engineer/Deep Learning Engineer/Optical Systems Engineer/Tracking Algorithm Specialist/Sensor Integration Engineer/R&D Engineer/ML Engineer/Algorithm Developer/Vision Software Engineer/Embedded Vision Engineer/Object Detection/Kalman Filter/Python/Blob Detection/Optical … Components/AI/ML/CV Development Engineer/AI Software Engineer/Machine Learning Engineer/Computer Vision Engineer/AI Research Engineer/ML Research Engineer/Computer Vision Software Developer ...

driven features, while contributing to the technical growth of the team. Responsibilities Responsibilities include: Bridge data science and software engineering to productionize AI/ML solutions. Collaborate with data scientists, software engineers, and product teams to deliver robust, scalable AI features for Workday Products. Integrate AI models into production systems … languages such as Python, Java, or C++, writing clean, efficient, and maintainable code for production-grade AI solutions. Hands-on experience deploying AI/ML models to production environments, with a good understanding of MLOps practices including CI/CD pipelines, model versioning, and monitoring. Experience with cloud platforms ...

languages such as Python, Java, or C++, writing clean, efficient, and maintainable code for production grade AI solutions. Hands-on experience deploying AI/ML models to production environments, with a good understanding of MLOps practices including CI/CD pipelines, model versioning, and monitoring. Experience with cloud platforms … Azure, or GCP) and cloud-native AI tools such as SageMaker, Vertex AI, or Azure ML Studio. Working knowledge of containerization technologies (e.g., Docker) and orchestration tools (e.g., Kubernetes) to build and manage scalable AI solutions. Skills in data engineering, including building data pipelines, data wrangling, and integrating AI solutions ...

pipelines, model serving, containerisation, orchestration, and environment management Sets the standard for reliability, observability, and operational excellence across the team's production AI/ML services Builds the tooling and paved paths that let AI engineers ship agentic AI and ML products safely and quickly Implements platform-level security, secrets … cloud-native deployment patterns Strong CI/CD experience and a track record of building deployment and release automation Experience serving, scaling, and monitoring ML models or data-intensive services in production (MLOps) Practical experience with observability tooling (metrics, logging, tracing) and production incident response Experience operating ML/ ...

language such as Java or C++), and a willingness to develop clean, maintainable code under guidance. Some exposure to deploying or supporting AI/ML models - through academic projects, internships, or early career experience - with an interest in developing MLOps skills (CI/CD, model versioning, monitoring). Awareness … risks to senior colleagues. Basic understanding of cloud platforms (AWS, Azure, or GCP); exposure to cloud-native AI tools (e.g., SageMaker, Vertex AI, Azure ML Studio) is a plus. Awareness of containerisation technologies (e.g., Docker); exposure to orchestration tools (e.g., Kubernetes) is beneficial but not essential. Emerging data engineering skills ...

Python, Java, or C++. Emphasis on writing clean, efficient, and maintainable code for production-grade AI solutions. Proven experience in deploying AI/ML models to production environments, ensuring scalability, reliability, and performance. Familiarity with MLOps practices, including CI/CD pipelines, model versioning, and monitoring. Comprehensive experience with cloud … platforms (AWS, Azure, or GCP) and cloud native AI tools, such as SageMaker, Vertex AI, or Azure ML Studio. Ability to design and deploy cloud-based AI solutions. Proficiency in using containerization technologies (e.g., Docker) and orchestration tools (e.g., Kubernetes) to build and manage scalable AI solutions. Strong skills ...

pipelines, model serving, containerisation, orchestration, and environment management Sets the standard for reliability, observability, and operational excellence across the team\'s production AI/ML services Builds the tooling and paved paths that let AI engineers ship agentic AI and ML products safely and quickly Implements platform-level security, secrets … cloud-native deployment patterns Strong CI/CD experience and a track record of building deployment and release automation Experience serving, scaling, and monitoring ML models or data-intensive services in production (MLOps) Practical experience with observability tooling (metrics, logging, tracing) and production incident response Experience operating ML/ ...

delivery — this is your chance to shape the intelligence behind the future of work. Join RoleMapper and lead the evolution of our AI and ML capabilities that make workforce decisions fairer, smarter, and more transparent. About RoleMapper In a world where organisations are facing significant skills challenges, increasing compliance requirements … phase of growth and position RoleMapper at the forefront of AI in work design. Responsibilities Translating product vision into a feasible, scalable AI and ML roadmap that delivers measurable business value and aligns with commercial goals. Designing and scaling RoleMapper’s AI and Machine Learning models, combining leadership ...

machine learning solutions across an evolving enterprise data environment. This is a hands-on role working across the full ML lifecycle, from prototype through to production, focused on delivering scalable, value-driven outcomes. Experience requirements & Responsibilities : Develop and deploy machine learning models to solve business problems. … Translate prototypes into production-ready solutions. Build and maintain data pipelines and ML infrastructure. Prepare and analyse large datasets, extracting actionable insights. Evaluate, optimise and monitor model performance. Support the design and delivery of AI initiatives. Work within Agile teams and engage with stakeholders across the business. Essential : Strong Python ...

augmented generation (RAG), named entity recognition (NER), prompt engineering, and personalization for content extraction, search, question answering, reasoning, and recommendation. Develop LLM, NLP, and ML solutions that address client requirements and drive business transformation. Work closely with partner teams—including Business, Technology, Product Management, Strategy, and Business Management—to deploy … reliability. Communicate results effectively to business stakeholders through written reports, visualizations, and presentations. Stay current with the latest research in LLM, agentic AI, ML, and data science, and proactively identify and leverage emerging techniques to drive ongoing enhancement. Qualifications, Capabilities, and Skills Proven experience applying NLP, LLM, and ML techniques ...

have a startup-like culture nurtured by sports and social clubs, being a safe place to fail, meaning and self-fulfilment over business, and learning from our partners, suppliers, and peers. We fully embrace DevOps ways of working in our teams, and build a very broad range of capabilities … challenges! It would be great if you also had experience in some of these, but if not we'll help you with them Machine Learning software e.g. Amazon and Azure machine learning, or Google's TensorFlow Deploying and managing in Cloud Computing such ...

keen ability to assess, analyse, and meet client-specific needs. You will play a major role in developing and implementing Machine Learning (ML) and Artificial Intelligence (AI) solutions for our clients, along with providing key advice around innovation and new techniques to stakeholders. You will be designing solutions … complex challenges and will integrate code with software engineers. Responsibilities will include: Leading and delivering technical consulting projects. Developing and delivering AI/ML solutions using a range of techniques (ML, NLP, LLMs, etc.) to tackle real world problems, applying tools and techniques, and developing novel approaches where required. Building ...

design. All underpinned by technology created with purpose. We’re looking for GenAI/Agentic Engineers who want to shape the future of Machine Learning, Generative AI and Agentic AI. You will be tasked with building and deploying intelligent systems that combine cutting-edge models, agentic frameworks … pitch contribution, and client hosting at events. Internal contribution – Campaign development, internal think-tanks, whitepapers, practice development (operations, recruitment, team events & activities), offering development. Learning & development – Training to support your career development and the skills demand within the company, certifications etc. YOUR PROFILE We’d love to meet someone ...

ensure best practices in modelling, experimentation and deployment. Data Science & Advanced Analytics – Design and implement predictive and prescriptive models for airline operations, applying machine learning, optimisation and statistical analysis to large, complex data sets. Translation of Business Problems – Convert business challenges into analytical frameworks and actionable solutions … collaboration, driving high‐impact projects and aligning with business objectives. Advanced knowledge of the Data Science Toolbox – mathematics, statistics, programming, data ingestion, munging, visualisation, machine learning, optimisation, simulation, reinforcement learning, and big‐data technologies. Experience leading successful data‐science projects in an operational setting (preferred). Understanding ...

culture. Ensure best practices in modelling, experimentation, and deployment. · Data Science & Advanced Analytics. Design and implement predictive and prescriptive models for airline operations. Apply machine learning, optimization techniques, and statistical analysis to large, complex datasets · Translate business problems into analytical frameworks and actionable solutions to improve decision making … advanced knowledge level of the Data Science Toolbox (i.e. the fundamentals of Mathematics and Statistics, computer programming, Data Ingestion, Data Munging, Data visualisation, Machine Learning, Optimisation, Simulation, Reinforcement Learning and Big Data techniques and technologies) · Have experience of leading and landing successful Data Science projects ...

Days Onsite) Salary + Benefits – £60,000 to £71,000 + 10% bonus, 33 days holiday, pension, healthCareer Progression + Modern Tech StackPyspark | ML | AI | Databricks | Kafka | AWSAre you a Data Engineer with strong Python, SQL and PySpark skills who is looking for the opportunity to step up and accelerate … ready to take on more responsibility, work on complex technical challenges, and gain exposure to cutting-edge technologies including Databricks, Kafka, Streaming, AI and Machine Learning.The OpportunityYou'll be joining a collaborative team of engineers and data specialists working on large-scale, real-time data platforms. This ...

keen ability to assess, analyse, and meet client-specific needs. You willplay a major role in developing and implementing Machine Learning (ML) and Artificial Intelligence (AI)solutions for our clients, along with providing key advice around innovation and new techniquesto stakeholders.You will be designing solutions for complex challenges … will integrate code with software engineers. Responsibilities will include: Leading and delivering technical consulting projects. Developing and delivering AI/ML solutions using a range of techniques (ML, NLP, LLMs, etc.)to tackle real world problems, applyingtools and techniques,and developing novel approaches where required. Building new relationships and maintainingcurrent ...

range of cross‐Bank communities on cloud, data science tools and AI. Role Requirements – Minimum criteria Advanced technical expertise in data science, machine learning or data engineering, including experience with Python and/or R. Strong understanding of cloud‐based technologies and solutions (Azure and Databricks preferred), DevOps … generative AI technologies including AI agents and their practical applications. Proven experience leading analytical projects that leverage large and complex datasets, applying data science, machine learning and AI techniques to derive actionable insights and support policy. Experience delivering business change and production‐ready pipelines through new data ...

support its growth. As Analytics Manager within the Chief Data Office, you’ll oversee all analytics activities—business intelligence, reporting, advanced analytics, and machine learning—across regions and functions. You’ll connect business needs with data solutions, ensuring insights are accessible, reliable, and impactful. Leading a global team … finance. Proven success in delivering impactful global analytics programs and leading diverse analytics teams. Expertise in defining requirements and managing advanced analytics and ML models for structured data. Proficient in Power BI, SQL, Python, Azure, Databricks, and Dataiku, with hands‐on ETL/ELT experience. Strong understanding of ML lifecycle ...

sourcing and hiring strategies. Build talent pipelines across multiple technology disciplines, including: Cloud Engineering Platform Engineering & Operations Software Engineering Data Engineering & Analytics Cybersecurity AI, Machine Learning & Generative AI Enterprise Architecture Infrastructure Engineering DevOps & Site Reliability Engineering Technology Risk & Governance Digital Transformation & Technology Modernisation Utilise LinkedIn Recruiter, networking, market … Experience supporting global technology organisations. Knowledge of cloud technologies (AWS, Azure, GCP), DevOps, cybersecurity, data platforms, and emerging AI technologies. Experience hiring for AI, Machine Learning, Generative AI, and cloud-native technology roles. Why Apply? Opportunity to recruit for cutting-edge technology teams. Exposure to large-scale enterprise ...

What you’ll be doing As Lead Data Scientist, you’ll combine deep technical work with strategic leadership: Design and deploy predictive models and ML solutions that power real-time markets. Work hands on with cutting-edge datasets, AI techniques, and scalable data pipelines. Identify patterns and insights that directly … return Fully remote working with flexibility built in. £90,000–£100,000 salary plus additional benefits. Access to huge, high-quality datasets and modern ML tooling. The chance to work on intellectually challenging problems every day. Real influence over large-scale analytical systems and strategy. Clear opportunities for career growth ...

contact the recruiter directly. Role Description You will lead one of our Claims Data Science agile squads, driving the delivery of innovative machine learning and data products that transform the customer journey and operational performance. This is a high-impact leadership role where you will shape data-driven … Collaborate with Scrum Masters to embed Agile principles and support a high-performing, self-organising team Champion the use of reporting, analytics, AI, and ML to enhance claims processes and customer outcomes Build strong relationships across IT, data, business teams, and global Allianz stakeholders Promote best practices in data architecture ...

diagrams to explain a data processing system on a cloud environment. Some knowledge of how you would present diagrams (C4, UML, etc.) Enthusiasm for learning and self-development. You have experience of working on agile delivery-lead projects and can apply agile practices such as Scrum, XP, Kanban. … engineers using a variety of techniques such as pair programming or mob programming. Working with data scientists to productionise advanced data deliverables, such as machine learning models Working knowledge of statistics Working with multidisciplinary digital and technology teams Working within the public sector Working with data scientists ...