1 to 25 of 4,723 Machine Learning Jobs in the UK

applications. Position Overview We are looking for a highly skilled Senior AI Software Engineer/AI Model Specialist with deep expertise in artificial intelligence, machine learning, and modern software development. The successful candidate will be responsible for designing, developing, training, testing, and optimizing AI models and intelligent software … collaborate with multidisciplinary teams to create innovative products that solve complex business and operational challenges. Key Responsibilities Design, develop, and deploy advanced AI and machine learning solutions. Build, train, validate, and optimize machine learning and deep learning models. Develop Generative AI and Large Language Model ...

with machine learning techniques. Always with an ethical and accurate lens. A Machine Learning & AI Engineer designing and deploying robust ML systems that bring data science to life through automation, CI/CD, and modern cloud engineering practices. Wherever you land, you’ll be working with … transform how the Bank serves customers and empowers colleagues. Data engineering, MLOps and intelligent automation, creating resilient data pipelines, scalable deployment architectures and automated ML workflows using contemporary engineering and CI/CD practices, enabling AI solutions to operate reliably across the enterprise. AI assurance, evaluation science and model governance ...

problems with machine learning techniques. Always with an ethical and accurate lens. A Machine Learning & AI Engineerdesigning and deploying robust ML systems that bring data science to life through automation, CI/CD, and modern cloud engineering practices. Wherever you land, you’ll be working with … Your personal learning plan could include Up to three Stanford Artificial Intelligence Professional Programmes Google Cloud certifications Coursera courses on everything from advanced ML to AI ethics and explainability And because your career is more than your day job, you’ll get stuck into side‐of‐the‐desk projects ...

with machine learning techniques. Always with an ethical and accurate lens. A Machine Learning & AI Engineer designing and deploying robust ML systems that bring data science to life through automation, CI/CD, and modern cloud engineering practices. Wherever you land, you'll be working with … Your personal learning plan could include: Up to three Stanford Artificial Intelligence Professional Programmes Google Cloud certifications Coursera courses on everything from advanced ML to AI ethics and explainability And because your career is more than your day job, you'll get stuck into side-of-the-desk projects ...

with machine learning techniques. Always with an ethical and accurate lens. A Machine Learning & AI Engineer designing and deploying robust ML systems that bring data science to life through automation, CI/CD, and modern cloud engineering practices. Wherever you land, you'll be working with … Your personal learning plan could include: Up to three Stanford Artificial Intelligence Professional Programmes Google Cloud certifications Coursera courses on everything from advanced ML to AI ethics and explainability And because your career is more than your day job, you'll get stuck into side-of-the-desk projects ...

coaching, and exposure that will accelerate your growth in ways you won’t find anywhere else. When you join us, you will have: Continuous learning: Our learning and apprenticeship culture, backed by structured programs, is all about helping you grow while creating an environment where feedback is clear … actionable, and focused on your development. The real magic happens when you take the input from others to heart and embrace the fast-paced learning experience, owning your journey. A voice that matters: From day one, we value your ideas and contributions. You’ll make a tangible impact ...

drift, and implement continuous improvement strategies. Communicate complex findings clearly to both technical and non-technical stakeholders. Stay current with advancements in AI/ML (LLMs, generative AI, reinforcement learning) and evaluate their potential impact on products. Key Skills & Experience: Experience in machine learning, data science … applied AI roles. Proficiency in Python and ML libraries (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch). Strong understanding of statistics, ML algorithms, and model evaluation techniques. Experience working with cloud platforms (AWS, Azure, or GCP) and ML pipelines. Ability to analyse large datasets and communicate insights effectively. Experience with LLMs ...

complex problems with machine learning techniques. Always with an ethical andaccuratelens. A Machine Learning & AI Engineer designing and deploying robust ML systems that bring data science to life through automation, CI/CD, and modern cloud engineering practices. Wherever you land,you’llbe working with some … Your personal learning plan could include: Up to three Stanford Artificial Intelligence Professional Programmes Google Cloud certifications Coursera courses on everything from advanced ML to AI ethics and explainability And because your career is more than your day job,you’llget stuck into side-of-the-desk projects ...

complex problems with machine learning techniques. Always with an ethical andaccuratelens. A Machine Learning & AI Engineer designing and deploying robust ML systems that bring data science to life through automation, CI/CD, and modern cloud engineering practices. Wherever you land,you’llbe working with some … Your personal learning plan could include: Up to three Stanford Artificial Intelligence Professional Programmes Google Cloud certifications Coursera courses on everything from advanced ML to AI ethics and explainability And because your career is more than your day job,you’llget stuck into side-of-the-desk projects ...

research. Strong software engineering skills, with a track record of building and maintaining production‐quality systems. Expert‐level Python experience with numerical, statistical, or ML libraries (e.g. NumPy, pandas, PyTorch, JAX, TensorFlow). Deep understanding of statistical modelling, optimisation, or machine‐learning techniques. Experience building and operating backend … systems and data pipelines in a cloud environment (e.g. AWS, GCP, or Azure). Experience validating, testing, and deploying quantitative or ML models. Comfortable working with high ownership in a small, senior team, partnering closely with Founders. Strong analytical judgement, communication skills, and attention to detail. Desired Experience with designing ...

Machine Learning, or Data Science are advantageous. Relevant certifications in cloud platforms (e.g., Microsoft Azure, Google Cloud Platform) and AI/ML engineering (e.g., TensorFlow Developer, Azure AI Engineer Associate) are desirable. Demonstrated commitment to continuous learning in AI system architecture, secure engineering, and cloud‐native development. … GenAI applications Strong hands‐on experience with cloud‐native AI development onMicrosoft AzureandGoogle Cloud Platform (GCP), including services such as Azure OpenAI, Azure ML, Vertex AI, and Gemini. Demonstrated ability to lead cross‐functional engineering teams across front‐end and back‐end disciplines. In‐depth understanding of secure engineering practices ...

agentic automation opportunities, define control and approval boundaries, iterate with users, and drive adoption through pilots, feedback loops, and measurable outcomes. Production AI/ML Integration: Build AI applications using LLM APIs, retrieval-augmented generation, embeddings, vector search, prompt and context management, structured outputs, response validation, and evaluation harnesses required … entitlement controls, observability, deployment automation, and cost and resilience trade-offs across AWS, Azure, or GCP. Demonstrated experience integrating LLM or AI/ML capabilities into production applications, including RAG pipelines, embeddings, vector databases or search indexes, prompt templates, context assembly, structured outputs, response validation, evaluation datasets, and model performance ...

seeking an AI Engineer for Autonomy to design, develop and deliver advanced Artificial Intelligence and Machine Learning solutions within complex and safety-critical environments. Working within a multidisciplinary AI and software engineering team, you will transform business and operational challenges into robust, scalable and secure AI capabilities. This … defence and technology programmes. KEY RESPONSIBILITIES: Translate business and operational requirements into AI solution designs and measurable outcomes. Develop, train and evaluate AI and Machine Learning models across areas such as computer vision, autonomy, large language models and predictive analytics. Design and maintain robust data processing, training ...

initiatives, AI solutions and emerging technologies. Evaluate technology development, change management, model governance, AI lifecycle management, data quality and cybersecurity controls. Review AI solutions, machine learning models and intelligent agents for governance, accountability, explainability, fairness, transparency and regulatory compliance. Perform risk assessments and identify emerging technology … Azure AI, Azure OpenAI, Snowflake, Dataiku or equivalent. Practical knowledge of Generative AI, Large Language Models, Retrieval Augmented Generation, Agentic AI, multi‐agent systems, machine learning or predictive analytics. Experience with AI and data solution lifecycle controls, including data quality, data lineage, model testing, prompt testing, access controls ...

bespoke analytics to be applicable to the broader investment sectors so that the solutions can be redeployed periodically. Stay current with developments in AI, machine learning, and data science, helping drive adoption of new capabilities across the investment platform. Qualifications, Experience & Attributes MSc, PhD, or equivalent degree … Mathematics, Statistics, Economics, Engineering, Computer Science, Data Science, Operations Research, or a related quantitative discipline. 5+ years' experience applying data science, machine learning, AI, or advanced analytics to solve complex commercial problems with measurable business impact. Strong programming skills in Python and SQL, with experience building robust analytical ...

automated testing in data engineering environmentsImplement observability and monitoring using tools like Databricks Workflows and related frameworksContribute to AI-driven initiatives by leveraging Databricks ML/MosaicML to integrate Generative AI and LLM-based solutionsRequirementsBachelor’s or Master’s degree in Computer Science, Software Engineering or related fieldExtensive experience designing … both technical and non-technical audiencesNice to haveExperience operationalizing LLM or Generative AI workflows in Databricks pipelinesFamiliarity with frameworks like LangChain, LlamaIndex or Databricks ML/MosaicMLKnowledge of AI governance, security practices and enterprise integration controlsBackground in financial trading data or related domainsOfficial Databricks certifications such as Certified Data Engineer ...

attack paths, blast radius, privilege escalation, lateral movement, toxic combinations, identity exposure, control gaps, and vulnerability prioritization. Build and evaluate graph algorithms and ML models including centrality, community detection, similarity, anomaly detection, node classification, link prediction, embeddings, and Graph Neural Networks. Design GraphRAG and knowledge-grounded security assistants that combine ...

responsible to the Head of AI, IPB Tech for the end-to-end design, build, and production delivery of priority IPB AI/ML use cases, with particular focus on agentic AI applications, generative AI guardrails, and production ML supporting advisor and client journeys. Job responsibilities Owns … delivery of priority IPB AI/ML use cases, from problem framing and business case through to deployed, monitored production services with measurable advisor and client impact Leads the engineering build of agentic AI and LLM-powered products serving IPB advisors and clients across international markets Sets the engineering quality ...

Data Science Manager Are you an experienced Data Science leader with a passion for building and scaling AI/ML products? Lead a team of exceptional Data Scientists and ML Engineers building next-generation AI solutions for financial markets. Drive innovation using LLMs, Generative AI, Deep Learning, Transformers, Agentic … with Engineering teams to productionize AI solutions and drive operational excellence. Build, mentor, and lead high-performing teams of Data Scientists and AI/ML practitioners. Set clear goals, drive accountability, and support career growth and development. Lead performance management, coaching, feedback, and talent development activities. Foster a culture ...

Looking For Proven experience leading the delivery of data science or AI projects from concept to production. Strong knowledge of Python and core ML libraries (e.g., spaCy, NumPy, SciPy, Transformers). Understanding of big data and cloud technologies (Spark, Hadoop, Azure, AWS, or GCP). Deep expertise in MLOps principles … Points For Experience in Banking or Financial Services. Exposure to GenAI, LLMs, and intelligent agent workflows. Experience with DevOps, CI/CD, and productionising ML systems. A passion for mentoring and developing early‐career data talent. Why Join Capco Deliver innovative, high‐impact data solutions for Tier 1 financial institutions. ...

Engineer to help turn pricing models and data science work into reliable production workflows. You’ll work with Pricing, Data Science, Data Engineering and ML Engineering teams to build pipelines that are easier to test, release, monitor and maintain. The role is hands‐on, with a focus on Python … testing and documentation. Make sure pipelines and model workflows are traceable, auditable and safe to change. Work closely with Pricing, Data Science, Data Engineering, ML Engineering and governance stakeholders. Technology and Ways of Working You’ll work in a modern data and machine learning environment. The role ...

years of industry experience across the globe. Sprytech has started an India office based in Mumbai and is working to establish an AI/ML driven cybersecurity and digital threat analytics centre to enhance the security of industry and government organisations. We are looking for an AI Application Developer … Qualifications Education: Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field. Experience: Proven experience in AI/ML model development and software engineering. Experience with end-to-end AI project deployment is highly desirable. Technical Skills Proficiency in programming languages such as Python ...

digital landscape. As an Associate Director Data Scientist in our growing Data & AI team, you’ll lead the design and delivery of advanced analytics, machine learning and Generative AI solutions, turning complex business and tax challenges into scalable, production-ready products and services. The role combines hands … into practical business solutions. Experience shaping Data & AI strategy, roadmaps and technical standards. Experience building reusable AI assets, frameworks or products. Strong understanding of ML/LLMOps, CI/CD, model monitoring and production deployment. Experience with agentic AI, RAG and knowledge-based systems. Experience operating within regulated or risk ...

RFPs, bids, client pitches and client events. Contributing internally through campaign development, think-tanks, whitepapers, offering development and practice growth, alongside your own funded learning, training and certifications. What You'll Bring Experience gained in a major consulting firm, or in industry with a consulting mindset comfortable … this role could be a great fit: GenAI Engineer, Generative AI Engineer, Agentic AI Engineer, AI Engineer, AI Consultant, Machine Learning Engineer, ML Engineer, Full Stack Engineer, Full Stack Developer, Python Developer, Senior Consultant Data Science, Data Scientist, Solutions Architect AI, LLM Engineer, MLOps Engineer, AI Software Engineer ...

research. Strong software engineering skills, with a track record of building and maintaining production‐quality systems. Expert‐level Python experience with numerical, statistical, or ML libraries (e.g. NumPy, pandas, PyTorch, JAX, TensorFlow). Deep understanding of statistical modelling, optimisation, or machine‐learning techniques. Experience building and operating backend … systems and data pipelines in a cloud environment (e.g. AWS, GCP, or Azure). Experience validating, testing, and deploying quantitative or ML models. Comfortable working autonomously in a small, senior team, partnering closely with Founders. Strong analytical judgement, communication skills, and attention to detail. Experience with designing and refining large ...