226 to 250 of 1,158 Machine Learning Jobs in the UK

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 ...

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 ...

White Collar Factory (95009), United Kingdom, London, London Engineering Manager – Software & ML About this role We are looking for a Software Engineering Manager who brings a solid foundation in modern development and some experience with Machine Learning environments . Be one of the first applicants, read the complete … integrate software features that are vital to the lives of credit card consumers. Nurture Talent: Coach and nurture your engineers, including those working on ML integration to achieve their technical, business, and personal goals. Bridge the Gap: Collaborate with Product Managers and Data Scientists to ensure ML models are effectively ...

days WFH per week) Your role: As a Data Scientist you will work on the company's core AI platform that enables data informed learning for students, from understanding student progress to using predictive modelling to recommend content and learning paths. You'll build models using diverse learning signals (written, spoken and behavioural data) and apply Machine Learning techniques across NLP, speech/audio and user interaction data. You'll have your voice heard, presenting your ideas to senior business stakeholders, defining 'undefinable' problems and uncovering insights via data. Location/WFH: You'll join ...

paced, collaborative environment. How You’ll Make an Impact: Design, build, and optimize risk models using our political risk data. Develop and maintain robust ML and data pipelines for experimentation and deployment. Prototype and test new approaches for extracting insights from unstructured data for corporate or financial markets. Collaborate cross … functionally with political scientists, data scientists, and backend developers. Explain ML/NLP model outputs and methodologies to non-technical stakeholders. You May be a Good Fit if: Proven experience developing, refining, and monitoring machine learning models. Substantial experience querying, cleaning, compiling, and analyzing big data . Familiarity ...

responsible AI solutions across a range of high-profile client engagements. Key responsibilities will include: * Designing and implementing end-to-end AI/ML solutions from development through to deployment and monitoring * Building scalable Generative AI and Agentic AI solutions, including RAG pipelines and orchestration frameworks * Implementing MLOps frameworks, governance … major Consulting firm, and/or in industry * A strong consulting mindset with experience engaging senior stakeholders * Proven experience designing and delivering AI/ML solutions at scale * Strong understanding of Generative AI, Agentic AI and modern AI engineering frameworks * Experience with at least one major cloud platform including Azure ...

advanced AI platform in their market. They help their clients serve customers with unmatched speed and accuracy. They’ve invested heavily into building the ML stack, partnered with leading universities, and trained models on millions of expert tagged images. Now, they’re scaling globally — and need a world-class Lead … experienced Lead Data Scientist to spearhead machine-learning initiatives, with particular focus on computer vision, large language models, and production ready ML pipelines in Azure. You will act as the technical lead for the team, setting direction, guiding best practices, and ensuring the successful delivery of high-impact ...

/London (hybrid) or remote from EU/UK What will you do Accelerate researchers by taking on the heavy parts of large‐scale ML pipelines and building robust tools. Interface cutting‐edge research with production: integrate checkpoints, streamline evaluation, and expose APIs. Conduct experiments on the latest deep‐learning techniques (sparsified 70 B + runs, distributed training on thousands of GPUs). Design, implement and benchmark ML algorithms; write clear, efficient code in Python. Deliver prototypes that become production‐grade components for Le Chat and our enterprise API. About you Master’s or PhD in Computer Science ...

Senior Software Engineer (ML Systems) Title : Senior Software Engineer (ML Systems) Company : Deep Technology Organisation Location : London Pay : Up to £120,000 Company : A deeply technical organisation is investing heavily in the future of large-scale intelligent systems. They are assembling a small group of exceptional engineers and researchers … deployed. In you, they hope to find a strong systems engineer with experience building or analysing high-performance computing platforms, distributed infrastructure, or machine learning systems. You will work alongside experts across software, infrastructure and research to shape the next generation of large-scale compute systems. There ...

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 ...

Senior AI/ML Research Engineer ( Azure AI foundry, Multi Agents and Azure Cloud ) £550-£700/day (max)Central LondonStarting July until 31st Dec 2026**No sponsorship – do not apply if you require sponsoring**Certain Advantage are recruiting on behalf of our global client for a Senior AI/… ML Research Engineer with experience in Azure AI foundry, Multi Agents and Azure Cloud solution development. The Role You’ll be a key member of the GenAI team within the responsible for designing, developing, and deploying scalable AI/ML solutions across multiple business areas.The role focuses on delivering production ...

Bachelor's degree (or equivalent experience) in Computer Science, Data Science, Engineering, Mathematics or a related STEM discipline. Proven substantial experience in AI/ML development, data science, or a related technology domain - including taking the lead in developing or evaluating complex AI solutions from concept through to implementation … these effectively on real-world projects. Excellent analytical, communication and leadership skills, with hands-on proficiency in programming and prototyping (e.g. Python, AI/ML libraries, data analysis tools), and an energetic, inquisitive and proactive approach with the integrity to thrive in a high-security, safety-first environment. Work hard ...

they need. Future-Facing Infrastructure: Building familiarity with Domins existing machine learning and data-driven workflows to help expand their AI/ML capabilities over time. Essential Requirements Education: A university degree in Computer Science, Software Engineering, Data Engineering, Data Science, or a related technical field. Python Skills … using Git. Beneficial Requirements Experience with cloud platforms (Azure is preferred, or AWS/GCP). An understanding of Docker and containerization. Familiarity with machine learning concepts and data preparation workflows. Experience contributing to database design or schema development. Familiarity with engineering, manufacturing, or test data environments. Strong ...

generate insights that support data-driven decision-making. The ideal candidate will have hands-on experience across SQL, Python or R, modern cloud platforms, machine learning techniques, and visualisation tools. They will be comfortable working in an agile environment, collaborating across teams, and ensuring the reliability, accuracy … dashboards and reports using Power BI or Tableau. Ability to translate analytical findings into compelling visual narratives for stakeholders. Desirable Skills Experience with additional ML interpretability methods (e.g., SHAP, LIME). Knowledge of CI/CD practices for data workflows. Understanding of data governance, lineage, and cataloguing tools. Exposure ...

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 ...

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 ...

London. In this pivotal role, you'll provide technical leadership across the full lifecycle of machine learning systems while architecting production-grade ML solutions. You will work with AWS SageMaker, lead teams on MLOps strategies, and ensure systems adhere to governance standards. This is a hands-on, technical … position ideal for those with deep expertise in ML frameworks such as PyTorch and TensorFlow, as well as experience in deploying scalable architectures. #J-18808-Ljbffr ...

methods to inform optimisation heuristics, demand forecasts, and dynamic decision‐support Machine Learning, Data Science & Applied AI Anomaly detection using statistical, ML, and hybrid methods for fault and quality monitoring. RUL estimation and predictive maintenance via survival, failure time, and degradation models. Time series forecasting and causal analysis … translating operational systems into models. Strong programming proficiency in Python (or similar languages) for data manipulation, automation, integration and working with AI/ML libraries. Demonstrated proficiency in at least one of the following: Modelling, Simulation & Digital Twins Optimisation Machine Learning, Data Science and applied AI techniques Solid ...

project delivery, stakeholder engagement, and supporting the development of others. For those at Consultant level, the role offers strong exposure to client work, learning from experienced practitioners, and a clear pathway for progression. We value curiosity, collaboration, and a growth mindset, and we encourage applications from candidates …/EPOS, digital, social and loyalty. AI Delivery Excellence – Proven experience owning workstreams including planning, execution, and successful delivery of insights or AI/ML POCs, MVPs and production grade solutions. Programming Experience - Skilled in using programming languages such as Python Cloud Expertise - Knowledge of cloud platforms and tools ...

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 … dedicated Career Manager to help you develop your career and guide you on your journey through BAE Don’t know a particular technology? Your learning and development is key to your future career and we provide a range of excellent training courses to enable you to upskill ...

knowledge graph systems. Ensure data quality, security, and compliance with governance standards. Collaborate with data scientists and architects to support graph-based analytics and machine learning use cases. Monitor, troubleshoot, and enhance data pipelines for performance and reliability. Contribute to best practices in data engineering, documentation, and data … complex technical concepts clearly. Proven ability to work collaboratively in distributed, global teams. Desirable Skills Experience with large-scale distributed data systems. Familiarity with machine learning pipelines and graph analytics. Understanding of data governance, metadata management, and semantic technologies. Experience working in Agile delivery environments. What We Offer ...

shipping code, but is comfortable influencing architecture, mentoring engineers, and shaping technical direction. You will have significant influence over: Core system architecture AI/ML strategy and implementation Data modelling and enterprise integration patterns Early product design decisions Engineering standards and scalability approach Key Responsibilities Design and build core components … technology environment (SaaS, AI platform, or similar) Proven ability to ship production-grade AI or data systems Strong Python engineering capability Experience with modern ML/LLM systems and frameworks Exposure to cloud-based AI/ML platforms (AWS, Azure, or GCP) Comfortable working in early-stage environments with ambiguity ...