51 to 75 of 3,211 Machine Learning Jobs in the UK

built in. Build platforms that support rapid experimentation while meeting production standards for latency, scale, monitoring, SLOs, playbooks, and operational excellence. Partner closely with ML engineers, product engineers, data scientists, and platform teams across DoorDash, Wolt, and the company to turn emerging GenAI capabilities into durable platform primitives. Shape … industry experience in software engineering Strong backend engineering fundamentals, especially in Python and distributed systems. Experience building production services, APIs, data pipelines, or ML infrastructure at scale. Experience operating systems in production, including observability, debugging, reliability, incident response, and performance/cost optimization. Hands‐on experience with LLM inference ...

Engineer (Machine Learning & NLP) Location: Fully Remote (UK) Salary: £60,000 - £70,000 + Benefits Type: Permanent Eligibility: Applicants must have the right to work in the UK. Unfortunately, sponsorship is not available for this position. The Opportunity We're looking for an AI Engineer to join … innovative team building cutting-edge AI and machine learning solutions. This is an exciting opportunity to work on large-scale AI platforms, helping to productionise machine learning models and develop cloud-native systems that power intelligent applications. You'll work closely with Data Scientists and Engineering ...

across the AI team, wider Consulting function and AI Community of Practice. Experience Required Essential Strong Python programming and hands‐on experience with core ML/AI libraries (for example scikit‐learn, TensorFlow, PyTorch). Practical experience developing, training and evaluating machine learning, NLP and predictive models. Experience … deploying AI/ML in the cloud, particularly Microsoft Azure (Azure AI/ML, Azure AI Foundry/Azure OpenAI). Working knowledge of Generative AI/large language models and prompt engineering applied to practical use cases. Understanding of MLOps practices for model deployment, monitoring and lifecycle management. Solid ...

winning the work, through to delivery governance and team leadership. You will bring SME-level depth in at least one of AI/ML Engineering, Platform Engineering, or Software Engineering, and apply it to create real, lasting value for our clients. Although we do not expect … advisors to our clients as well as bringing deep technical knowledge when needed. The profile of our typical engagements reflect that. AI/ML Specialism You will bring expert-level knowledge in at least one of the following domains, and working knowledge across the others: Agentic AI & LLM Engineering Design ...

directly. Requisition ID36775Office CountryUnited KingdomOffice CityLondonDivisionInformation TechnologyFull TimeContract TypeFixed TermContract Length3 yearsPosting End Date31/08/2026 Accountabilities & Responsibilities The Principal, AI/ML Engineer leads the design, delivery and continuous improvement of AI and ML solutions within their area of responsibility, aligning engineering activities to the Bank … strategic direction while taking accountability for translating this into practical, high-quality engineering outcomes across squads. Leads the definition and execution of AI/ML engineering direction across one or more squads, ensuring alignment with the Bank’s AI strategic vision, as set out by the AI Capability Lead ...

seeking a Software Engineer with expertise in AWS and Python, and a passion for Machine Learning, to help engineer and deploy innovative ML solutions into production. You will join the Applied AI/ML Software Engineering team, collaborating with technology teams across the firm, contributing to both … support of the firm's business objectives. In this role, you will work alongside Data Scientists to build cloud‐based frameworks for hosting machine learning models, providing software engineering expertise throughout the model development lifecycle. You will leverage both internal and external cloud platforms, utilizing proprietary and open ...

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/ ...

clients, understanding their needs, and translating them into effective outcomes. Key Responsibilities Design, develop, and maintain high-performance Java-based applications Integrate AI/ML models into production-grade backend systems Build RESTful APIs and microservices using modern Java frameworks Collaborate with data scientists to deploy and scale machine … deploy AI-powered services Contribute to architecture decisions and technical roadmaps Design, develop, and maintain high-performance Java-based applications Integrate AI/ML models into production-grade backend systems Build RESTful APIs and microservices using modern Java frameworks Collaborate with data scientists to deploy and scale machine learning ...

others to deliver advanced AI and data solutions at citizen scale. Our 150-strong AI and Data Practice brings together deep expertise in machine learning, generative AI, agentic AI and data. We are pioneers in responsible AI, having authored the UK government's AI Cyber Security Code … 2.1 degree in Computer Science, AI, Data Science, Statistics or in a similar quantitative field. Demonstrable experience of deploying modern AI/ML solutions into production, including prompt engineering, retrieval-augmented generation (RAG), model evaluation, and monitoring using metrics (e.g. precision, recall, NDCG and drift detection). Strong Python skills ...

Enterprise Architect — Artificial Intelligence AI/ML Infrastructure, Platform & Governance Role Summary World Wide Technology is looking for a deeply technical Enterprise Architect who will own the delivery of AI projects end to end from the silicon and data center design that underpins AI workloads, through the software and MLOps … while mentoring delivery teams and shaping WWT's broader AI point of view. Key Responsibilities Own end-to-end technical delivery of AI/ML engagements: architecture definition, design authority, build oversight, and go-live validation. Host and chair Architecture Review Board (ARB) and Technical Design Authority (TDA) sessions ...

Fuzzy Labs is a fast-growing, Manchester-based tech consultancy that helps a diverse range of clients productionise machine learning using Open Source MLOps. We exist to help our customers harness and channel the power of AI safely and effectively, to make positive change … good. Our work sits across the whole development lifecycle, from prototyping new machine learning models to building scalable and secure production ML systems, and everything in between. Our work spans disruptive startups, multi-national organisations, policing, and secure government sectors, providing you with the unique opportunity to make ...

others to deliver advanced AI and data solutions at citizen scale. Our 150-strong AI and Data Practice brings together deep expertise in machine learning, generative AI, agentic AI and data. We are pioneers in responsible AI, having authored the UK government's AI Cyber Security Code … Computer Science, AI, Data Science, Statistics or in a similar quantitative field. Proven experience of leading multi-disciplinary teams to deliver AI/ML solutions to production. Demonstrable experience of technical leadership for AI delivery including architecture, product design principles and engineering excellence. Experience with the latest AI engineering approaches ...

validate predictive models and build efficient, automated processes for delivering modelling results at scale Apply modern machine learning capabilities — including AI/ML, deep learning, NLP, causal ML, and explainable AI — across multiple data modalities and clinical development contexts Apply statistically rigorous approaches to clinical trial data … machine learning models on high-dimensional data for time-to-event, longitudinal, and multivariate outcomes Experience in the application of AI/ML and proficiency in Python, R, SQL , and cloud platforms (e.g., AWS, Azure, Databricks) Familiarity with clinical trial design, drug development processes, and the role ...

validate predictive models and build efficient, automated processes for delivering modelling results at scale* Apply modern machine learning capabilities — including AI/ML, deep learning, NLP, causal ML, and explainable AI — across multiple data modalities and clinical development contexts* Apply statistically rigorous approaches to clinical trial data … machine learning models on high-dimensional data for time-to-event, longitudinal, and multivariate outcomes* Experience in the application of AI/ML and proficiency in **Python, R, SQL**, and cloud platforms (e.g., AWS, Azure, Databricks)* Familiarity with clinical trial design, drug development processes, and the role ...

twice per week, with flexibility to work remotely three days p/w. What you'll be doing: Clinical Prediction Models: Design and implement ML models predicting patient outcomes including medication adherence, treatment response, adverse event risk, and clinical deterioration Patient Stratification: Build risk stratification models identifying patients who would … from clinical interventions, medication therapy management, or enhanced monitoring Treatment Optimization: Develop models recommending optimal treatment pathways, medication alternatives, and personalized clinical interventions Healthcare ML Best Practices: Ensure models meet healthcare standards for interpretability, clinical validation, and regulatory requirements (FDA guidance on clinical decision support) Product-Embedded Analytics: Lead integration ...

career adventure where your ideas matter and your skills drive change. As a Senior Lead Software Engineer, Cloud Platform in the Corporate AI and Machine Learning Data Platforms team, you will design and deliver secure, high-quality technology solutions that support our data and analytics strategy. You will … infrastructure-as-code technologies. Experience implementing multi-cloud architectures and leading end-to-end platform development. Background in designing and developing scalable AI/ML or Data platforms. Experience with automation and workflow orchestration for operational efficiency.Published contributions to open-source or industry-recognized projects. Hands-on experience building ...

platforms. You will leverage your expertise in Databricks, Apache Spark, and Azure to design, develop, and implement data warehouses, data lakehouses, and AI/ML models that fuel our data-driven operations.What You Will Be DoingWe are looking for strong Data and Solution Architects who are passionate and focused … legacy systems to scalable, cloud-native solutions.Design and implement lakehouse architectures that unify data lakes and data warehouses for advanced analytics and AI/ML workloads.Partner with other solution architects to assess solution alignment to the overall architectural blueprint – and drive proposal writing, solution direction, pricing and costingOwns Solution Development ...

designing highly available Hybrid and Multi-Cloud architectures (Azure & AWS). AI & Machine Learning Exposure: Experience designing architectures that support AI/ML workloads, including integrating Large Language Models (LLMs), predictive analytics, and vector search into enterprise applications. Enterprise Governance & Security: Deep understanding of security architecture, secure SDLC … landscape, notably encompassing: Compute & Services: Java, .NET, Python, Cloud-native microservices; Data & Analytics: Databricks, Microsoft Fabric, AWS Glue, Athena, Event Streaming (e.g., Kafka); AI & ML: Azure OpenAI, LLM Integration patterns, Vector Databases; Integration & Storage: Azure Data Factory (ADF), SQL Server, Enterprise relational platforms; Infrastructure: Azure, AWS, and Hybrid Cloud networks. ...

designing highly available Hybrid and Multi-Cloud architectures (Azure & AWS).* AI & Machine Learning Exposure: Experience designing architectures that support AI/ML workloads, including integrating Large Language Models (LLMs), predictive analytics, and vector search into enterprise applications.* Enterprise Governance & Security: Deep understanding of security architecture, secure SDLC … technology landscape, notably encompassing:Compute & Services: Java, .NET, Python, Cloud-native microservicesData & Analytics: Databricks, Microsoft Fabric, AWS Glue, Athena, Event Streaming (e.g., Kafka)AI & ML: Azure OpenAI, LLM Integration patterns, Vector DatabasesIntegration & Storage: Azure Data Factory (ADF), SQL Server, Enterprise relational platformsInfrastructure: Azure, AWS, and Hybrid Cloud networksCandidates ...

clients. Join our engineering teams that build massively scalable software and systems, architect low latency infrastructure solutions, proactively guard against cyber threats, and leverage machine learning alongside financial engineering to continuously turn data into action. Create new businesses, transform finance, and explore a world of opportunity … coordinate multi‐step diagnostic and remediation tasks. AIOps & Intelligent Observability: Ability to integrate traditional observability stacks (e.g., Datadog, Prometheus, OpenTelemetry) with AI/ML models to automate root‐cause analysis, anomaly detection, and semantic log clustering. Self‐Healing Infrastructure Engineering: Experience designing closed‐loop, self‐healing systems that autonomously execute ...

Experience building or integrating AI-powered applications and services. Familiarity with Large Language Models (LLMs), Generative AI, Retrieval-Augmented Generation (RAG), AI agents, or machine learning workflows. Experience integrating AI APIs and platforms such … OpenAI, Anthropic, Azure AI, or similar technologies. Knowledge of vector databases, embeddings, prompt engineering, and AI application architecture. Experience with Python for AI/ML-related development. Exposure to MLOps practices and AI model deployment pipelines. Contributions to open-source projects or technical communities. Competitive Salary Bonus Scheme Private Healthcare ...

contribute to the design, deployment, and iteration of our next-generation benefits platform features that leverage personalization, experimentation, and AI/ML methods (e.g. agents/LLMs, recommender systems, reinforcement learning) to enhance user experience in a meaningful business domain. Contribute across the tech stack : You’ll work …/TypeScript) on the frontend and Python (FastAPI, SQLAlchemy) on the backend, shipping production-ready code and user-facing features in addition to innovative ML work. Live on the cutting edge of AI tooling : You’ll help push the boundary of what’s feasible with modern AI-powered software development ...

solutions that enable analytics, automation, and AI-driven business outcomes. Develop and optimise Snowflake-based data platforms to support reporting, data science, and machine learning workloads. Create automated, reliable, and observable data pipelines that meet engineering, governance, and security standards. Collaborate with stakeholders and technical teams to promote … best practices in SQL, Python, data modelling, and AI development. Drive the adoption of AI, machine learning, and generative AI technologies to deliver innovative business solutions. Continuously improve platform performance, scalability, and operational efficiency while supporting AI governance and MLOps best practices. Unfortunately we are unable to progress ...

risk, counterparty credit risk, regulatory risk capital and derivative valuation adjustments. Using the latest analytics and technology such as a fully vectorized pricing library, Machine Learning, and a Big Data stack for scalability, our products and solutions are used by the largest tier-one banks to smaller niche … historical market data, pricing services, scenario generation, or analytics input validation. Experience with observability, production support, automated controls, regression testing, reconciliation, model input validation, machine learning, NLP, or responsible AI applications in financial analytics. CFA, FRM, CQF, or other relevant professional qualification. About S&P Global Market Intelligence ...

your expertise in AWS analytics and data integration services to design, develop, and implement modern data architectures and pipelines that fuel analytics, AI/ML, and data-driven operations.* Design and build high-performance data integration solutions: Use AWS Glue, AWS Step Functions, Amazon EventBridge, and AWS Database Migration Service … governance practices using Amazon S3 (data lake), AWS Lake Formation, Amazon Redshift, and Amazon Athena to ensure trusted data.* Ability to design AI/ML-enabled solutions: Enable feature-ready, governed datasets for data science and integrate with Amazon SageMaker (and related AWS AI services) to operationalise models and drive ...