126 to 150 of 3,232 Machine Learning Jobs in the UK

understanding of (Intune, Workspace ONE, JAMF) and how AI enhances device experience. Strong knowledge and firsthand experience of deploying/implementing of AI/ML concepts, including LLMs, chatbots, predictive analytics, and automation frameworks. Associate and professional level certifications in Microsoft 365, Azure AI, Google Cloud, or ServiceNow. Experience delivering … well-being holistically, supporting our people’s physical, mental, and financial health. We also provide opportunities to keep skills relevant through certifications, learning, and diverse work experiences. We’re proud to be consistently recognized as one of the World’s Best WorkplacesTM. Join Accenture to work at the heart ...

Learning and statistical modeling. Primary concentration on credit risk modeling, also encompassing utilization, pricing, collections, and marketing optimization. Collaborate with a team of ML Scientists to manage the lifecycle of ML models from experiment design to deployment and monitoring. You will have the freedom to innovate with data, methodologies … Responsibilities Collaborate with Credit Strategy Managers, Model Validation Analysts, Backend Engineers, and Product Managers to integrate model development into the product roadmap. Own several ML applications from experiment design to deployment and monitoring. Decide on impactful topics across Borrowing products and deliver solutions. Technology Stack Google Cloud Platform for analytics ...

team is key to our success. We're people-first. We value collaboration, curiosity and commitment. As a Principal Software Engineer - Applied AI ML Director at the company within the Accelerator Business, you are the heart of this venture, focused on getting smart ideas into the hands of our customers. … vector stores such as Pinecone, GCP RAG engine, and AWS S3 Vector Buckets Exposure to cloud-native microservices architecture Familiarity with advanced AI/ML concepts and protocols, including Retrieval-Augmented Generation (RAG), agentic system architectures, and Model Context Protocol (MCP) Hands-on experience with agentic frameworks (LangChain, CrewAI, AutoGen ...

looking for talented people who will shape how millions of customers play, watch, and connect every day. As a Senior Engineer in our ML Platform squad, you will drive the development of a brand-new ML Platform for the whole Engineering organisation at Super Technologies. You will enable adoption … ML and AI across all teams and tribes, with your work directly impacting platform security, user experience, and large-scale data‐driven decision‐making for hundreds of thousands of users daily. This role blends hands‐on technical work with strategic thinking — you will lead by example, contribute high‐quality code ...

Data Science. 4+ years of experience in engineering, with 2+ years in customer‐facing or field roles. Proven success building and deploying AI/ML or data‐intensive applications in production. Deep full‐stack development skills (Python, Node.js/Go, React/Vue) and DevOps experience (Docker, K8s, CI/ ...

environments. Experience with cloud platforms such as Azure, AWS or GCP. Understanding of cybersecurity for connected devices and IoT systems. Exposure to AI/ML technologies and data-driven applications. Experience with mobile, web, IoT, Embedded Linux, Python, FPGA or MATLAB development. Why Join Us? You'll have the opportunity ...

financial services tech teams. Not a fit if you: Don't hold a degree from the top-tier universities listed above. Are a pure ML engineer or data scientist without a strong software engineering track record. Have less than 5 or more than 12 years of professional experience. Are frontend ...

enterprise systems via APIs and data pipelines, with strong security, data governance and residency practices. Cloud: AWS, Azure or GCP, including managed AI/ML services. Delivery: Agile, CI/CD, modern SDLC and TDD. Data and architecture: Modelling across relational, columnar and vector stores, grounded in sound architectural principles. ...

clients and business partners around the world. Job responsibilities Design, build, and maintain scalable data platforms and pipelines that support analytics and AI/ML use cases. Own and optimise Retrieval-Augmented Generation (RAG) pipelines to enable LLMs to safely and accurately use enterprise data. Implement and integrate GenAI capabilities ...

shelf LLMs, bespoke fine-tuned models, and sometimes techniques that utilise no LLM at all. This means you will Train, evaluate, and iterate on ML models and agentic systems for customer feedback, including owning our custom fine-tuning pipelines. Run experiments end-to-end, track results rigorously, and make clear … collaborate closely with Engineering on productionisation, model serving, data pipelines, and monitoring. Work with Product and Commercial teams to translate business needs into practical ML solutions, and support client evaluations and accuracy benchmarking. Mentor team members, review code and research, and bring relevant advances from the literature into the product. ...

build production-ready AI features that empower business users to leverage the power of GenAI within their planning workflows, requiring both deep ML knowledge and strong software engineering skills. Your Impact Lead the architecture, design, and deployment of scalable Generative AI and Machine learning systems into production environments. … production environments Implement monitoring, logging, and observability for GenAI systems to track usage, errors, and model behaviour Collaborate with data scientists to productionise ML models and forecasting algorithms Your Skills Extensive hands-on professional experience in the field of Artificial Intelligence, Machine Learning, or related engineering domains. ...

Leadership & Execution: Drive the technical roadmap for Search, Retrieval, Ranking, and Recommendation systems within the Trips vertical. Translate high‐level business goals into concrete ML architectures and scalable production systems. Advanced Algorithm Innovation: Design, prototype, and scale next‐generation recommendation and ranking models. Solve complex, non‐linear travel journeys … closely with Product Managers, Engineering Leads, and Data Science peers to optimize multi‐task business objectives simultaneously. Act as the primary technical authority for ML initiatives within the Trips vertical. Talent Multiplier: Mentor and coach senior and mid‐level ML scientists. Foster a culture of technical excellence, driving best practices ...

support of the CODAS project and related R&D Lab initiatives. Contribute to the delivery of technical components for a sovereign AI ecosystem, including ML services, data processing pipelines, evaluation tooling and deployment‐ready applications. Support the translation of research outputs into robust, maintainable and operationally viable systems. Work with … internal colleagues and external project partners to understand technical requirements, constraints and delivery priorities. Help adapt AI and ML approaches to privacy‐sensitive, security‐conscious and regulated deployment contexts. Contribute to the integration of technical solutions into project infrastructure, workflows and partner environments. Troubleshoot technical, data and integration issues arising ...

financial services, primarily mortgage lenders, including nine of the top 10 mortgage providers. At Hometrack, we are looking for an experienced Senior Machine Learning Engineer, to translate POC model code from data science and analytics into robust pipelines and live APIs. Responsibilities Oversee the deployment of machine learning models into production, ensuring they perform well in real-world conditions and monitoring their performance over time. Work closely with data scientists, software engineers, product managers, and stakeholders to integrate machine learning solutions into our products and services. Develop automated workflows for model retraining, testing ...

build, and deploy machine learning and statistical models using Azure Machine Learning Studio (AML Studio) in production environments. Apply appropriate ML techniques to improve predictions such as longevity, default risk, and investment outcomes. Machine Learning Operations (MLOps in Azure) Manage the full ML life … cycle using Azure ML Studio, including deployment, monitoring, retraining pipelines, and version control. Implement robust MLOps practices such as model drift detection, data quality monitoring, and automated retraining workflows. Data Engineering and Preprocessing Develop and maintain scalable data pipelines using Python, SQL, and Azure Data Factory (ADF). Ensure data ...

delivery of machine learning systems at Super Technologies. By combining cutting‐edge applied machine learning, foundational research, and seamless ML operations, the team harnesses data to revolutionize the online gambling and sports betting experience. From predictive analytics and personalization to fraud detection and real‐time recommendations … gaming or entertainment industry Experience working with tools and technologies such as Spark, Snowflake, Qwak, MLFlow, Airflow, etc Contributions to open‐source AI/ML projects or participation in AI/ML competitions (e.g., Kaggle) Experience with training and fine‐tuning large‐scale foundation models (e.g., GPT, BERT ...

join a global team focused on building real-world data science and AI solutions for Risk & Trading workflows. This role will span predictive modelling, machine learning, and modern AI systems powered by large language models. This is an opportunity to own projects end-to-end, from problem framing … grade solutions. Key Responsibilities Build and deliver solutions across predictive analytics, machine learning, and LLM-based AI. Design, develop, and implement bespoke ML and AI agents and multi-step workflows using modern frameworks such as LangChain, LangGraph, or similar technologies. Develop robust, scalable, production-grade Python code. Partner ...

sales Senior Technical Solutions Engineer (AI/ML - Digital Native Business) x2 London, United Kingdom Req ID: FEQ327R439 x 2 New roles Recruiter: Dina Hussain Location: London (or surrounding areas) At Databricks, our core values are at the heart of everything we do; creating a culture of proactiveness … independently operating Solutions Architect. What we look for Experience, technical customer‐facing and with a background ideally in Data Science/Generative AI/Machine Learning , but will also consider Data Warehousing or Data Engineering. You will be working in the following any of the following vertical sectors ...

help our users know their body better. The job We are looking for a Senior Software Engineer with deep expertise in AI/ML infrastructure to join our AI Platform team and help build the GenAI platform that powers every AI feature at Flo. You will bridge core infrastructure, data … directly with technology partners on pre-release capabilities Experience and Skills Must have Engineering maturity: 7+ years of software engineering, 4+ years focused on ML/AI platforms LLM experience: recent hands‐on work with at least one of: fine‐tuning, prompt engineering, LLM evaluation, or model serving Technical stack ...

MLOps Engineer to join our Data & Compute Platform team based in London. What You’ll Do Own and manage the full lifecycle of both ML models and core infrastructure - from development and deployment to monitoring and continuous improvement. Build and maintain robust CI/CD pipelines for both software … ML workflows. Ensure reliability, scalability, observability, and security of production systems and ML infrastructure. Automate deployment, orchestration, and environment management using modern DevOps tooling. Collaborate closely with software engineers, data scientists, and product teams to bring ML-powered features to production. Proactively detect, troubleshoot, and resolve infrastructure and model performance ...

enjoy turning ambiguity into reliable production systems, you'll thrive here. Join a team that values craft, security, and learning. As an Applied AI ML Lead in LLM Suite Engineering, you will design and deliver production-grade AI/ML and agentic solutions that integrate seamlessly with existing systems. … algorithms that integrate with existing systems Create architecture and design artifacts for complex applications, ensuring design constraints are met through delivery Build AI/ML solutions and agentic systems for the LLM Suite platform using public cloud architecture (Azure, AWS) and modern agentic frameworks Implement GenAI services leveraging Azure OpenAI ...

performance, scalability, and security. Participate in code reviews and provide constructive feedback to peers. Stay up to date with emerging Cloud and AI/ML technologies and industry trends to drive innovation and continuous improvement Lead communities of practice across Software Engineering to promote awareness and adoption … software engineering concepts and applied experience Experienced in cloud development (AWS), with a focus on application design and development. Experience with AI/ML model integration, Prompt engineering, LLM APIs (OpenAI, Bedrock) and Generative AI Advanced in Java and Python Strong experience with cloud platforms like AWS, Azure, or Google ...

enjoy turning ambiguity into reliable production systems, you’ll thrive here. Join a team that values craft, security, and learning. As an Applied AI ML Lead in LLM Suite Engineering, you will design and deliver production-grade AI/ML and agentic solutions that integrate seamlessly with existing systems. … algorithms that integrate with existing systems Create architecture and design artifacts for complex applications, ensuring design constraints are met through delivery Build AI/ML solutions and agentic systems for the LLM Suite platform using public cloud architecture (Azure, AWS) and modern agentic frameworks Implement GenAI services leveraging Azure OpenAI ...

build, and deploy scalable machine learning algorithms and software solutions. Analyse, cleanse, and normalise complex time-series data and dynamical systems. Integrate ML models into production using cloud platforms and modern JavaScript frameworks. Collaborate within an Agile environment to deliver robust data structures and algorithms. What … engineering and data science capabilities: Core Development: Proficiency in Python, JavaScript, and Java, alongside modern frameworks (React, Redux, Vue, or Angular). Data Science & ML: Solid understanding of common ML techniques, trade-offs, and scalable ML architecture (MapReduce, streaming). Data Expertise: Experience with time-series data, dynamical systems ...

microservices, event‐driven design, and managed services, ensuring reliability, observability, and scalability. Provide architectural leadership across integrations with enterprise systems and third‐party platforms. ML Ops, Reliability & Engineering Best Practices Productionize AI and machine learning solutions using modern ML Ops and software engineering practices. Establish standards for testing … with Infrastructure as Code, microservices, and event‐driven architectures. Strong grounding in statistics, experimentation, and analytical methods. Experience deploying and maintaining production AI/ML systems, including monitoring and governance. Solid understanding of secure system design, data privacy, and enterprise engineering practices. Excellent communication skills with the ability to influence ...