226 to 250 of 1,202 Machine Learning Jobs in the UK

scientific R&D capability. This is a rare opportunity to join a rapidly growing, venture-backed business that combines advanced sensor technology, AI/ML, data science and chemical sensing to build products capable of detecting and interpreting biological and environmental signals in ways not previously possible. The company … limitations and deployment suitability Working closely with hardware and engineering teams on sensor integration Collaborating with data scientists to interpret sensor outputs and improve ML models Helping turn early-stage concepts into scalable commercial products Supporting the development of the company's growing sensing and AI platform Influencing future hiring ...

propose and deliver across our rapidly growing Financial Services Business unit. This is a pivotal role, requiring you to balance deep AI and machine learning expertise with commercial and strategic leadership. We’ll look to you to define a differentiated technical vision for clients across banking, insurance … other media Who we're looking for: You are an experienced technology leader, with a proven track record of successfully leading AI/ML strategy and project delivery You bring a strong understanding of MLOps, with experience deploying commercially valuable AI applications within the financial services sector You have experience ...

pivotal role in defining how some of the UK's largest organisations adopt and scale AI. From Generative AI and autonomous agents to machine learning and enterprise data platforms, you'll be at the forefront of designing solutions that move beyond proof-of-concepts into real-world impact. … architecture of complex AI solutions, working across discovery, design, implementation and scale. Lead the architecture of enterprise AI, Generative AI and Machine Learning solutions Design intelligent agent frameworks and next-generation AI-powered applications Define AI governance, security and Responsible AI standards Advise executive stakeholders on AI strategy ...

Fraud team at Wise is dedicated to safeguarding our platform against financial crime and ensuring the protection of our legitimate customers. Leveraging cutting-edge machine learning, real-time transaction monitoring, and data analysis, our team is responsible for developing and enhancing fraud detection systems. Software engineers, data analysts … vision is: Build a globally scalable fraud prevention and detection engine to maintain Wise as a secure environment for our legitimate customers. Utilise machine learning techniques to identify potential risks associated with customer activity. Foster a strong partnership between our fraud investigators and the product team to develop ...

opportunity for a technically strong architect who can hit the ground running from day one, providing architectural leadership across enterprise data platforms, analytics initiatives, machine learning capabilities and emerging AI solutions. You'll be responsible for defining and governing data architecture standards, designing scalable data solutions, and ensuring … Senior Data Architect capacity Strong expertise in data architecture, data modelling and information management Experience designing modern data platforms supporting analytics, reporting and machine learning workloads Knowledge of data governance, lineage, metadata management and data quality frameworks Experience defining technical standards, patterns and architectural principles Excellent stakeholder management ...

opportunity for a technically strong architect who can hit the ground running from day one, providing architectural leadership across enterprise data platforms, analytics initiatives, machine learning capabilities and emerging AI solutions. You'll be responsible for defining and governing data architecture standards, designing scalable data solutions, and ensuring … Senior Data Architect capacity Strong expertise in data architecture, data modelling and information management Experience designing modern data platforms supporting analytics, reporting and machine learning workloads Knowledge of data governance, lineage, metadata management and data quality frameworks Experience defining technical standards, patterns and architectural principles Excellent stakeholder management ...

opportunity for a technically strong architect who can hit the ground running from day one, providing architectural leadership across enterprise data platforms, analytics initiatives, machine learning capabilities and emerging AI solutions. You'll be responsible for defining and governing data architecture standards, designing scalable data solutions, and ensuring … Senior Data Architect capacity Strong expertise in data architecture, data modelling and information management Experience designing modern data platforms supporting analytics, reporting and machine learning workloads Knowledge of data governance, lineage, metadata management and data quality frameworks Experience defining technical standards, patterns and architectural principles Excellent stakeholder management ...

opportunity for a technically strong architect who can hit the ground running from day one, providing architectural leadership across enterprise data platforms, analytics initiatives, machine learning capabilities and emerging AI solutions. You'll be responsible for defining and governing data architecture standards, designing scalable data solutions, and ensuring … Senior Data Architect capacity Strong expertise in data architecture, data modelling and information management Experience designing modern data platforms supporting analytics, reporting and machine learning workloads Knowledge of data governance, lineage, metadata management and data quality frameworks Experience defining technical standards, patterns and architectural principles Excellent stakeholder management ...

seamless deployment. Our expertise spans the full AI lifecycle — from data advisory, data collection, labeling and annotation, RLHF, and AI training data to advanced machine learning, AI agents, voice AI, robotics data services, and enterprise AI applications. With Arabic-first, domain-specific innovation, CNTXT AI delivers practical … Surge AI TELUS Digital DataForce Sama Invisible Technologies Or have sold: AI Training Data Data Annotation Services RLHF Services Enterprise AI Solutions AI Infrastructure Machine Learning Services AI Agents Voice AI Platforms Required Qualifications 10+ years of enterprise sales experience. 5+ years in sales leadership positions. Proven experience ...

encompasses the products and systems closest to the customer journey - search, pricing, payments, fare intelligence, and conversational interfaces. You will define and lead the ML strategy, team, and delivery across this domain. That means building and scaling ML and AI capabilities that measurably improve the customer experience and drive business … outcomes. The work spans traditional ML systems and emerging agentic/LLM-based capabilities. You will lead multiple ML teams through their respective team leads, reporting to the Director of AI & ML. You’ll be accountable for the people (2 ML Managers and ~10 ICs), delivery, and budget across your ...

consideration to driving action. As a Senior MLOps Engineer you will play a critical role in building the operational infrastructure that brings AI and ML models into production at Global:IQ. You will own the platforms, pipelines and processes that enable Data Science and Applied ML teams to deploy, monitor … capabilities. This position demands a hands-on engineer with deep expertise in operationalising machine learning systems, a strong understanding of cloud infrastructure, ML lifecycle management, and production monitoring. You will work closely with Data Scientists, Data Engineers and Product teams to create robust, scalable and maintainable MLOps workflows ...

Recursion’s drug discovery platform. From model training pipelines to production deployment systems, to agent infrastructure and Large Language Models, you will ensure our ML models can operate at massive scale across our supercomputing infrastructure, both on‐prem and in the cloud. You will work cross‐functionally across ML engineering … data science, and research teams to translate requirements into robust, scalable ML infrastructure solutions. In This Role You Will: Enable AI/ML, LLM, and Agentic Systems teams for scale – build and operate platforms that allow data scientists and ML engineers to train, deploy, and monitor models across Recursion ...

actively to codebases and architectural decisions Developing and deploying production-grade AI systems using Azure, Databricks and Generative AI tooling Owning the implementation of ML pipelines, APIs and data integration workflows Enforcing MLOps best practices, coding standards, version control and performance optimisation Collaborating cross-functionally with data scientists, product managers … Python proficiency (async programming, concurrency, multithreading) Expertise in RESTful API design, OpenAPI/Swagger documentation and API lifecycle best practices Hands-on experience with ML libraries: PyTorch, PySpark, scikit-learn, Hugging Face Transformers Proficiency in AI tooling: Azure ML, Databricks, MLflow, LangChain, LangGraph Proven experience with Git, unit testing, containerisation ...

high‐impact problems end‐to‐end. Build end‐to‐end production‐ready pipelines from ideation to deployment. Key Responsibilities Develop and deploy large‐scale ML and GenAI‐powered products and pipelines. Own all stages of the data science project lifecycle: develop, deploy, monitor, and scale models through the full Software … Development Life Cycle, perform exploratory data analysis, proof‐of‐concepts, model benchmarking, and validation experiments for both ML and GenAI approaches, partner with business leaders, domain experts, and end‐users to gather requirements and align on success metrics, follow coding standards, perform code reviews, optimize data science workflows, and evaluate ...

research that supports both our applications and the broader scientific community Current areas of interest include large language models (LLMs), optimization methods for deep learning, reinforcement learning (RL), and generative models. Key Responsibilities Shape and communicate the strategic vision for research across the organization Oversee multiple high-impact … research projects and ensure alignment with organizational goals Drive breakthroughs in machine learning and artificial intelligence through innovative re-search Mentor and provide leadership to senior researchers and research teams Represent the team in external partnerships, collaborations, and policy discussions Influence organizational research priorities and contribute to policy ...

Lead high-impact data science initiatives end-to-end, including problem framing, methodology selection, experiment development, implementation partnership, and impact measurement. Build and deliver machine learning and reinforcement learning solutions to improve player engagement, retention, monetization, and operational outcomes. Lead the modeling framework for complex systems, guaranteeing … related quantitative field, or equivalent experience in practice. Experience: 5+ years of professional data science experience. You have delivered at least 3 data or ML products from problem definition to production deployment and monitoring. Demonstrated proficiency in clustering, predictive modeling, reinforcement learning, and Bayesian statistics. Hands-on experience ...

hiring in Miami, London and Milan. Description -- Role: expected to contribute to production grade proprietary trading systems, deploy state of the art AI/ML, develop novel AI/ML models, experiment with and develop novel trading ideas, explore new datasets. -- Required: experience training ML models end to end (from … data processing to fine tuning), experience training across transformers/generative models/RL, publications in either top tier ML conferences (e.g., NeurIPS, ICLR, ICML, JMLR, etc.) or top scientific journals, top tier institutions/industry experiences. -- Positives but not requirement: PhD. Reference: AMC/AHU/NW/SPH001 ...

flows, connectors and agent behaviours, defining secure, scalable solution architectures. Build and maintain AI components (e.g. RAG, classification, recommendation, summarisation) using Python and modern ML/LLM frameworks. Implement end-to-end MLOps pipelines for development, testing, deployment and monitoring of Copilot and AI solutions, and deploy them into production … about you... Degree in Computer Science, Data Science, Software Engineering, Mathematics, Engineering or a closely related field. Previous experience in AI, data science, ML engineering or advanced analytics. hands-on experience designing, building and deploying Copilot and/or agentic AI solutions (e.g. Microsoft 365 Copilot extensions, Azure OpenAI-based ...

market. The product team is ambitious and well-resourced, with a long-term roadmap and real appetite for innovation - including AI and machine learning integration. The Role You'll be the voice of the user across the product team - owning the research programmes that shape product direction … research - interviews, surveys, observational studies, and usability evaluations Translating findings into personas, journey maps, wireframes, prototypes, and user flows Designing UX for AI and machine learning-powered features, including efficacy testing and governance Running usability tests, iterating on designs based on evidence Collaborating with product managers, engineers ...

interactive workshop to teach artificial intelligence concepts through guided exercises and discussion Serve as a thought leader, evangelizing the benefits of AI testing & reinforcement learning Maintain deep understanding of competitive and complementary technologies and vendors and how to position Braze in relation to them Collaborate cross-functionally (e.g., sales … engaging presenter: You are an enthusiastic and engaging presenter, with the ability to communicate effectively with a wide range of stakeholders An expert in machine learning: You have a solid grasp of machine learning, including a familiarity with reinforcement learning Mar-tech savvy: You understand ...

experience. We are assembling a small, senior team of researchers and engineers obsessed with systems-first intelligence. Our current team consists of PhDs and ML engineers from top applied ML and coding agent companies, with a heritage of shipping systems at Spotify, ShareChat, and Sourcegraph scale. Our team has built … comfortable reading a NeurIPS paper as you are debugging a distributed system. Core Qualifications Experience & Impact: 4+ years of experience in Applied Science or ML Engineering, with a clear track record of shipping ML products that directly impacted top-line business metrics (e.g., retention, engagement, revenue) at scale (100M+ users ...

needs. You will also influence senior stakeholders, shape roadmaps, and drive measurable outcomes across the organisation. Responsibilities Set AI and data science strategy across ML, NLP, search, recommendation, experimentation, and generative AI, aligning work to product goals, customer needs, and business priorities. Lead and develop high-performing teams by coaching … cross-functional leaders, shaping roadmaps, translating technical insights, and aligning teams on customer and business impact. Requirements Significant experience in data science, AI/ML, NLP, information retrieval, statistics, or a related quantitative field, or equivalent practical experience. Strong technical expertise across modern data science methods, including machine learning ...

SeniorML Systems Engineers - Vision ML/Visual Data Processing A privately backed AI technology company operating at the intersection of machine learning in the media industry. You will own core ML infrastructure end to end, from data ingestion and curation through to distributed training and production inference, working … scale multimodal datasets (video, embeddings, metadata). This is not a research role. The focus is on productionising models, building reliable platforms, and making ML systems fast and scalable in a real production environment. The ideal profile is an ML engineer transitioning from research into platform ownership - someone ...

partner teams; avoid duplication, ensure accountability. Collaborate with Product Managers to embed AI capabilities into broader product strategies. Work closely with Data Scientists, ML Engineers, and MLOps teams to ensure technical feasibility and scalability. Act as the primary liaison between business stakeholders and AI team. Educate stakeholders on AI capabilities … field; advanced degree desirable. Knowledge & Experience Demonstrable experience of AI product delivery/ownership within insurance or financial services. Strong understanding of AI/ML concepts, model lifecycle, and MLOps. Knowledge of ethical AI principles and regulatory frameworks. Stakeholder influence, structured problem-solving, commercial acumen, clear communication, and change leadership. ...

date with its features, capabilities, and roadmap Tungsten Solutions Knowledge : Maintain a firm understanding of all primary Tungsten Automation solutions and offerings AI and ML Capabilities : Leverage AI and machine learning capabilities, including natural language processing (NLP), computer vision, and LLMs, to optimize document processing, data extraction … term success of Tungsten Automation solutions Production AI Experience : Leverage experience with deploying, monitoring, and maintaining AI/LLM models in production (e.g., Azure ML, AWS Sagemaker, or Kubernetes-based ML pipelines) Thought Leadership : Provide thought leadership on AI-driven automation trends and best practices, both internally and externally Collaboration ...