876 to 900 of 1,050 Machine Learning Jobs in the UK

deployment across regulated financial environments. Key Responsibilities Design AI and GenAI architecture strategies and roadmaps that align with enterprise objectives. Build scalable AI/ML and Agentic AI platforms, working across large language models (LLMs), retrieval-augmented generation (RAG), embeddings, and semantic search. Support AI deployment, governance, and integration patterns … vector databases, MLOps/LLMOps, AWS, Azure, GCP, Databricks, Kubernetes, and GPU infrastructure. What We're Looking For Proven experience designing enterprise AI or ML architectures, with a strong understanding of cloud and modern data platforms. Demonstrable exposure to scalable AI deployment and integration patterns is essential, as is experience ...

lean development processes, engineering metrics (DORA, SPACE, etc.), and delivery predictability while maintaining velocity.Innovation & Technology : Stay ahead of industry trends (cloud-native, AI/ML, microservices, etc.) and evaluate new technologies that can drive business value.Risk & Compliance : Oversee technical risk management, data privacy, security standards, and regulatory compliance (SOC2, GDPR … concepts for non-technical executives.Strategic thinking combined with strong execution and operational rigor.Data-driven decision making using engineering metrics and KPIs.Experience with AI/ML integration or modern frontend/mobile stacks is a plus.What Success Looks LikeEngineering organization consistently delivers high-impact features on time with high quality.Low employee ...

development processes, engineering metrics (DORA, SPACE, etc.), and delivery predictability while maintaining velocity. Innovation & Technology: Stay ahead of industry trends (cloud‐native, AI/ML, microservices, etc.) and evaluate new technologies that can drive business value. Risk & Compliance: Oversee technical risk management, data privacy, security standards, and regulatory compliance (SOC2 … technical executives. Strategic thinking combined with strong execution and operational rigor. Data‐driven decision making using engineering metrics and KPIs. Experience with AI/ML integration or modern frontend/mobile stacks is a plus. What Success Looks Like Engineering organization consistently delivers high‐impact features on time with high ...

integration architecture, covering API management, event-driven patterns (Kafka, EventBridge), messaging (JMS, MQ), ETL/ELT pipelines, microservices and service mesh topologies. Champion AI, ML and agentic automation opportunities within the trading technology estate including intelligent scheduling, anomaly detection, automated P&L attribution, predictive maintenance and agentic workflow orchestration (e.g. … migration planning. Working knowledge of Foundry (Palantir) or equivalent analytical platforms for downstream data consumption, operational analytics and decision support. Experience architecting AI/ML and agentic automation solutions within trading technology estates, including LLM integration, RAG patterns, intelligent scheduling and predictive analytics. Familiarity with Agile/SAFe delivery frameworks ...

signal processing (e.g. MEMS microphones, accelerometers) Develop RF communication systems (LoRa/LPWAN, mesh networking) Implement secure communications (encryption, authentication, secure boot) Deploy optimised machine learning models on embedded devices Essential Experience Strong embedded C/C++ development experience Full product lifecycle … experience (concept to production) Low-power system design expertise Sensor data processing and RF communications (LoRa or similar) Embedded security and debugging skills Desirable ML for acoustic detection MEMS microphone systems OTA updates and noise mitigation Start-up experience If you're looking to build intelligent, low-power sensing systems ...

data in real-time, the structuring, storage and processing of that data for insight, to the usage of the data in event driven applications, ML and AI. As a Senior Manager Architect in Data you will be an experienced technical leader bringing business, industry and deep technical understanding to shape … specific expertise in Distributed Data Processing architectures (Spark, PySpark, Python, Airflow), ELT data processing underpinning Data LakeHouses and Data Products for scaled use within ML & AI Expertise in Streaming Data, Event Driven Design, Data Governance & the AWS Cloud Technology stack (e.g. Glue, ServerLess, DynamoDB) A track record in leading ...

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 ...

robust and explosive DataOps business. Series C funded (raised over $60m this year ). They have built a product that leans into blending machine learning models and data annotation to help businesses save time and money! What You’ll Get This is a key hire ...

driven initiatives. * This role will suit someone with a strong foundation in AWS data engineering and BI, alongside practical exposure to AI/ML concepts or tools. * Design, build and optimise data pipelines and data platform components within AWS * Support and enhance Business Intelligence reporting and analytics capabilities * Contribute … services (e.g. AWS Bedrock or similar) * Supporting AI-enabled data products or workflows * Understanding of generative AI/prompt engineering concepts * Exposure to ML pipelines or collaborating with Data Science teams * Typically 4-8+ years' experience in data engineering/BI roles * Proven experience delivering AWS-based data solutions ...

metrics that drive engineering decisions anddemonstrateplatform health to stakeholders Champion AI and modern data tooling —you'llpush the boundaries ofwhat'spossible, with hands-on ML product experiencerequiredand LLMexpertisea serious bonus. Join us on a mission to become the best data company in telematics. If you're ambitious, passionate about data … data products Advanced Python (PySparkor Polars preferred) and SQL across multipleflavours— comfortable owning and evolving live production codebases Hands-on experience building and shipping ML products, not just prototyping Deep familiarity with Azure Data Lake and file-based storage architectures Strong Git discipline and version control best practices A genuine ...

full-stack shop consisting of product and portfolio leadership, data engineering, infrastructure and DevOps, data/metadata/knowledge platforms, and AI/ML and analysis platforms, all geared toward: Building a next-generation, metadata- and automation-driven data experience for GSK's scientists, engineers, and decision-makers, increasing productivity … reducing time spent on "data mechanics" Providing best-in-class AI/ML and data analysis environments to accelerate our predictive capabilities and attract top-tier talent Aggressively engineering our data at scale, as one unified asset, to unlock the value of our unique collection of data and predictions ...

frameworks Embed data quality checks by default (schema validation, completeness, freshness, thresholds, alerting) Improve pipeline resilience, monitoring, observability and recovery mechanisms Integrate AI/ML capabilities where appropriate (e.g. anomaly detection, intelligent monitoring) Support delivery of a wider Data Strategy programme , improving consistency and data quality Ensure pipelines are production … strong SLAs Exposure to AI-enabled data pipelines (e.g. anomaly detection, intelligent monitoring) Experience with data quality at scale Understanding of MLOps or deploying ML models into production Must-Haves Strong hands-on experience with GCP, Python and Scala Proven track record delivering production-grade data pipelines Deep expertise across ...

into business workflows to deliver measurable commercial impact. The responsibilities of the Chief Data & Analytics Office include advancing both traditional AI/ML and generative AI capabilities, identifying priorities and focusing on high-impact AI use cases, setting the GenAI strategy around LLMs and Agentic AI, reusing and scaling … experience with diverse problem-solving background required – e.g. top strategy consulting firm, internal strategy, investment banking, private equity Deep knowledge and understanding of AI&ML preferred (esp. how to use GenAI tools/Prompt Engineering, retrieval-augmented generation (RAG) and agentic workflows) BSc or MSc degree in relevant field Outstanding ...

Full Stack Engineer – ML/GenAI Our trusted partner, which operates within the Ed-Tech domain, employs over 10,000 individuals across 100 countries, and has a reach of 600 million users, is recruiting a Full Stack Engineer with hands-on development capabilities in Python, JavaScript/TypeScript and ML … Experience in software development and architecture, with a track record of delivering high-quality, scalable software applications, is desirable. Experience working on AI/ML/LLM-based applications is desirable. Beneficial technical skills include: AWS – including certification Terraform Kubernetes Data science/ML tooling – scikit, TensorFlow, hugging face, pytorch ...

Data Science/ML Engineer (Contract) Glasgow (1 day per week) 600/day (Outside IR35) 3 Months We're hiring a hands-on ML Engineer to help a growing data-led marketing business unlock the value of its dataset across lead generation and tender platforms. The role: Building intelligent … enrich CRM data and extract insight from transcription data. Identify key data signals driving revenue and optimise over time. Deploy solutions in a cloud ML environment (GCP/Vertex AI) What we're looking for: Strong commercial Data Science/ML experience. Python and cloud ML platforms (GCP/Vertex ...

integration. Frameworks: Hands-on experience building GenAI applications using LangChain and LangGraph (agent architecture design, state management, and graph-based workflow orchestration). ML & Cloud Ecosystems: Solid understanding of ML algorithms, FastAPI, PyTorch/TensorFlow, MLflow, MLOps practices, containerization (Docker, Kubernetes/AWS EKS), and cloud services (AWS Bedrock, SageMaker ...

data Creating reports, data pipelines, dashboards, and AI agents Supporting digital and data life-cycle improvement projects Assisting with forecasting and predictive analysis through ML models Working with different departments to translate business challenges into data solutions. Learning programming (SQL, Python, DAX and others), analytics, and data science techniques ...

business outcomes. Key responsibilities: Translating business objectives into AI architecture strategies, roadmaps and scalable solution designs Designing and implementing end to end AI and ML architectures across enterprise environments Defining scalable, performant and cost optimised deployment patterns across cloud, containerised and GPU enabled environments Supporting AI implementation programmes from proof … transformation programmes Producing solution design documentation, implementation plans and technical proposals Providing technical leadership and mentoring within multidisciplinary teams Experience Required: Experience designing AI, ML or modern data architectures within enterprise environments Strong understanding of cloud platforms such as AWS, Azure, GCP, Databricks or similar technologies Experience architecting scalable ...

business outcomes. Key responsibilities: Translating business objectives into AI architecture strategies, roadmaps and scalable solution designs Designing and implementing end to end AI and ML architectures across enterprise environments Defining scalable, performant and cost optimised deployment patterns across cloud, containerised and GPU enabled environments Supporting AI implementation programmes from proof … transformation programmes Producing solution design documentation, implementation plans and technical proposals Providing technical leadership and mentoring within multidisciplinary teams Experience Required: Experience designing AI, ML or modern data architectures within enterprise environments Strong understanding of cloud platforms such as AWS, Azure, GCP, Databricks or similar technologies Experience architecting scalable ...

business outcomes. Key responsibilities: Translating business objectives into AI architecture strategies, roadmaps and scalable solution designs Designing and implementing end to end AI and ML architectures across enterprise environments Defining scalable, performant and cost optimised deployment patterns across cloud, containerised and GPU enabled environments Supporting AI implementation programmes from proof … transformation programmes Producing solution design documentation, implementation plans and technical proposals Providing technical leadership and mentoring within multidisciplinary teams Experience Required: Experience designing AI, ML or modern data architectures within enterprise environments Strong understanding of cloud platforms such as AWS, Azure, GCP, Databricks or similar technologies Experience architecting scalable ...

rapid productisation, and clear business accountability. Applied AI Delivery Oversee the design and delivery of production AI systems – agentic workflows, LLM‐powered co‐pilots, ML inference pipelines, embedded into live front‐office operations. Ensure solutions integrate seamlessly with core systems and existing architectures. Drive the transition from proof‐of‐concept … scalable, enterprise‐grade deployment with measurable adoption and impact. Data & Platform Strategy Own the Applied AI platform strategy, including real‐time data pipelines, ML feature stores, model registries, and agentic runtime and control plane infrastructure. Partner with relevant teams and stakeholders to ensure a coherent, governed AI foundation. Governance, Risk ...

require a Data Science Consultant to join their Defence & National Security team. You will design, build, and deploy scalable data pipelines and AI/ML solutions that directly support vital national security projects. In order to be successful, you will have the following experience: Experienced in the Python data stack … ready data engineering pipelines Utilise AWS-based infrastructure and services to deploy and manage data workflows Evaluate and implement a variety of AI and ML solutions to solve complex client problems, integrating models smoothly into production systems Creative visualisation techniques to design impactful, intuitive data visuals and dashboards Adhere ...

driven initiatives. This role will suit someone with a strong foundation in AWS data engineering and BI, alongside practical exposure to AI/ML concepts or tools. You must have strong hands-on experience in: AWS Data Engineering stack (e.g. Glue, S3, Lambda, Redshift, Athena) SQL (advanced level) Python … Terraform, APIs, CI/CD beneficial) Experience working in Business Intelligence/analytics environments Candidates must demonstrate some level of exposure to AI/ML, such as: Working with cloud-based AI services (e.g. AWS Bedrock or similar) Supporting AI-enabled data products or workflows Understanding of generative AI/ ...

platform and accelerate our transformation. The Opportunity You will work closely with our 46-strong engineering team, guiding and influencing how AI, ML, and LLM-based technologies are embedded into our product, processes, and pricing models. Your work will be project-driven, and highly visible — with the unique satisfaction … demonstrate: Either a track record of implementing and documenting CLI & MCP services and advanced AI workflows. or hands-on experience building and deploying ML or Deep Learning pricing/analytical models. You are familiar with Python, AWS and the use of obvious AI platforms such as GPT, Opus, Gemini ...

market operates. This is not a research role — we need someone who ships. What You Will Do Lead the design and delivery of complex ML and GenAI systems — robust, scalable, and built for production. Guide the team across the full AI lifecycle, from experimentation and evaluation through deployment and monitoring … cash flow waterfalls, ABS/CLO structures, and priority of payments. Strong software engineering skills (Python preferred) combined with deep knowledge of AI/ML frameworks, GenAI tooling, and modern data infrastructure. Hands‐on experience building and deploying ML/GenAI systems in production within finance, legal, or other high ...