401 to 425 of 4,514 Machine Learning Jobs in England

represent Deloitte in client leadership forums.The following will be an added advantage:Relevant certifications in cloud and AI (e.g., AWS, Azure or GCP; machine learning or data engineering certifications).Experience establishing responsible AI practices (governance, risk and controls) for generative AI and advanced analytics.Consulting experience leading multi-workstream ...

represent Deloitte in client leadership forums.The following will be an added advantage:Relevant certifications in cloud and AI (e.g., AWS, Azure or GCP; machine learning or data engineering certifications).Experience establishing responsible AI practices (governance, risk and controls) for generative AI and advanced analytics.Consulting experience leading multi-workstream ...

world.As a Machine Learning Engineer at Autodesk Research, you will work side-by-side with researchers and engineers to build and enable ML-powered capabilities in Autodesk products. You are an ML engineer with strong software engineering skills who is passionate about solving problems and building things … working model from our offices in London.ResponsibilitiesCollaborate on projects at the intersection of research and product with a diverse, global teamBuild and iterate on ML pipelines, prototypes, and evaluation workflows, enabling rapid deployment and testing of experimental modelsWork with complex datasets and representations for model training, evaluation, and analysisAnalyze errors ...

beyond proof of concept into secure, production-grade deployment. The role: - Design AI and GenAI architecture strategies and roadmaps - Build scalable AI/ML and Agentic AI platforms - Work across LLMs, RAG, embeddings and semantic search - Support AI deployment, governance and integration patterns - Collaborate with engineering, data, DevOps and business … Vector databases MLOps/LLMOps AWS/Azure/GCP/Databricks Kubernetes & GPU infrastructure What you'll bring: - Experience designing enterprise AI or ML architectures - Strong grasp of cloud and modern data platforms - Exposure to scalable AI deployment and integration patterns - Financial Services or regulated industry experience (essential) - Strong ...

Solution Architects through to senior technical leadership. What you'll be doing Designing AI and GenAI architecture strategies and roadmaps Building scalable AI/ML and Agentic AI platforms Working across LLMs, RAG, embeddings and semantic search Supporting AI deployment, governance and integration patterns Collaborating with engineering, data, DevOps … frameworks Vector databases and semantic search MLOps and LLMOps AWS, Azure, GCP, Databricks Containerisation, Kubernetes and GPU infrastructure Requirements Experience designing enterprise AI or ML architectures Strong understanding of cloud and modern data platforms Exposure to scalable AI deployment and integration patterns Financial Services or regulated industry experience essential Strong ...

Solution Architects through to senior technical leadership. What you'll be doing Designing AI and GenAI architecture strategies and roadmaps Building scalable AI/ML and Agentic AI platforms Working across LLMs, RAG, embeddings and semantic search Supporting AI deployment, governance and integration patterns Collaborating with engineering, data, DevOps … frameworks Vector databases and semantic search MLOps and LLMOps AWS, Azure, GCP, Databricks Containerisation, Kubernetes and GPU infrastructure Requirements Experience designing enterprise AI or ML architectures Strong understanding of cloud and modern data platforms Exposure to scalable AI deployment and integration patterns Financial Services or regulated industry experience essential Strong ...

wide goals Drive architectural decisions and technical excellence across teams Ensure robust systems for deployment, monitoring, scalability, and reliability of infrastructure supporting AI/ML workloads Collaborate with engineering leaders globally to align on technical standards, best practices, and cross‐site initiatives Team Building & Talent Build and scale high‐performing … office Deep technical expertise in distributed systems, cloud platforms (AWS, GCP, or Azure), and infrastructure automation Experience with infrastructure supporting large‐scale AI/ML systems, including: GPU infrastructure and orchestration ML training and inference pipelines Model serving and deployment at scale Strong understanding of modern infrastructure technologies: Kubernetes, Terraform ...

frameworks Experience in building AI business, solutions and competency • Experience in GenerativeAI, LLM and prompt engineering Exsentive experience in technology within in AI/ML leadership role Strong hands on experience with ML frameworks Experience with cloud platforms(AWS, AZURE) Deep understanding of ML algorithms, LLMs and AI architecture Proven … adoption Experience in driving AI-first thinking across the organization. Proven experience in leadership and team building: Build, mentor and scale AI/ML/Data Science teams and establish best practices for model development, deployment and governance. Proven ability to foster a culture of experimentation, innovation and continuous learning. ...

team player and work collaboratively with the business and the team.Connect to your skills and professional experience Essential:Experience full-stack software or ML engineering with strong Python Development practices (CI/CD, testing, muti-threading/asynchronous execution, PEP8 etc.)Experience designing, testing and deploying production-scale AI/… ML solutions (APIs, microservices, cloud deployment, endpoint deployment, registries, pipelines)Experience with LLM based applications (NLP, embeddings, semantic search, RAG, Graph RAG, fine-tuning)Proficient in ML tools and modern ecosystem (PyTorch, MLFlow, FastAPI, SQL Alchemy)Experience retrieving data from structured, unstructured and web sources (Selenium/PlayWright, Pandas ...

transform the way biomedical professionals carry out their research and day‐to‐day exploration. What you’ll be doing Design and implement ML/AI solutions end‐to‐end, from the idea and data exploration phase to deployment and monitoring, balancing cutting‐edge techniques with pragmatism to deliver measurable impact. … reliable, maintainable, production‐ready and can be readily adapted to future developments. Choose the right approach for the problem at hand, evaluating classical ML and NLP techniques, LLM‐based solutions, and agentic solutions to balance trade‐offs between speed, cost, complexity, interpretability, and performance. Collaborate closely with product, design ...

apply AI to transform the way biomedical professionals carry out their research and day-to-day exploration.What you’ll be doing· Design and implement ML/AI solutions end-to-end, from the idea and data exploration phase to deployment and monitoring, balancing cutting-edge techniques with pragmatism to deliver … reliable, maintainable, production-ready and can be readily adapted to future developments.· Choose the right approach for the problem at hand, evaluating classical ML and NLP techniques, LLM-based solutions, and agentic solutions to balance trade-offs between speed, cost, complexity, interpretability, and performance.· Collaborate closely with product, design ...

example Python, C#, JavaScript, Kotlin, Java or Go)Experience with Gen AI tools (such as LangGraph, CrewAI, Hugging Face or OpenAI APIs) and ML frameworks like PyTorch or TensorFlowStrong understanding of ML fundamentals (training, evaluation, deployment) and LLM-specific challenges such as prompt engineering, latency and cost optimisationExperience with cloud ...

Production Solution Delivery: Lead impactful customer technical projects by delivering production‐grade systems, designing and building reference architectures, custom applications and data ingestion and ML/AI model integration Transformational Impact: Guide strategic customers as they implement transformational big data projects including end‐to‐end design, build and deployment … with distributed computing with Apache SparkTM and knowledge of Spark runtime internals Familiarity with CI/CD for production deployments Working knowledge of MLOps, ML/AI models and AI APIs Design and deployment of performant production end-to-end data architectures and applications that combine data pipelines, ML/ ...

Production Solution Delivery: Lead impactful customer technical projects by delivering production-grade systems, designing and building reference architectures, custom applications and data ingestion and ML/AI model integration Transformational Impact: Guide strategic customers as they implement transformational big data projects including end-to-end design, build and deployment … with distributed computing with Apache SparkTM and knowledge of Spark runtime internals Familiarity with CI/CD for production deployments Working knowledge of MLOps, ML/AI models and AI APIs Design and deployment of performant production end-to-end data architectures and applications that combine data pipelines, ML/ ...

Production Solution Delivery: Lead impactful customer technical projects by delivering production-grade systems, designing and building reference architectures, custom applications and data ingestion and ML/AI model integrationTransformational Impact: Guide strategic customers as they implement transformational big data projects, including end-to-end design, build and deployment of industry … oneDeep experience with distributed computing with Apache Spark and knowledge of Spark runtime internalsFamiliarity with CI/CD for production deploymentsWorking knowledge of MLOps, ML/AI models and AI APIsDesign and deployment of performant production end-to-end data architectures and applications that combine data pipelines, ML/ ...

architectures and orchestration frameworks (e.g., LangGraph, AutoGen, CrewAI); tool‐use patterns, human‐in‐the‐loop workflows, and agentic safety at enterprise scale. AI/ML Engineering & MLOps: Full AI/ML lifecycle ownership—training pipelines, model deployment, versioning, monitoring, drift detection, observability (e.g., Weights & Biases, Arize), and lifecycle management using … such as MLflow, Vertex AI, or SageMaker. Cloud AI Platforms: Demonstrated deployment of AI workloads on AWS, GCP, and/or Azure including managed ML services, scalable inference infrastructure, and vector stores. Programming & Frameworks: Strong Python proficiency; working knowledge of PyTorch or TensorFlow; applied experience with AI application frameworks (LangChain ...

architectures and orchestration frameworks (e.g., LangGraph, AutoGen, CrewAI); tool-use patterns, human-in-the-loop workflows, and agentic safety at enterprise scale* AI/ML Engineering & MLOps: Full AI/ML lifecycle ownership: training pipelines, model deployment, versioning, monitoring, drift detection, observability (e.g., Weights & Biases, Arize), and lifecycle management using … such as MLflow, Vertex AI, or SageMaker* Cloud AI Platforms: Demonstrated deployment of AI workloads on AWS, GCP, and/or Azure including managed ML services, scalable inference infrastructure, and vector stores* Programming & Frameworks: Strong Python proficiency; working knowledge of PyTorch or TensorFlow; applied experience with AI application frameworks (LangChain ...

agent architectures and orchestration frameworks (e.g., LangGraph, AutoGen, CrewAI); tool-use patterns, human-in-the-loop workflows, and agentic safety at enterprise scaleAI/ML Engineering & MLOps: Full AI/ML lifecycle ownership: training pipelines, model deployment, versioning, monitoring, drift detection, observability (e.g., Weights & Biases, Arize), and lifecycle management using … platforms such as MLflow, Vertex AI, or SageMakerCloud AI Platforms: Demonstrated deployment of AI workloads on AWS, GCP, and/or Azure including managed ML services, scalable inference infrastructure, and vector storesProgramming & Frameworks: Strong Python proficiency; working knowledge of PyTorch or TensorFlow; applied experience with AI application frameworks (LangChain, LlamaIndex ...

ensuring traceability, documentation accuracy, and compliance. Ensure solutions meet compliance standards (e.g. ISO 27001). AI & Data Awareness Ensure solution designs support AI/ML-enabled capabilities where relevant (e.g. data lineage, governance, feature management, and model integration patterns). Collaborate with wider technical teams to define integration approaches … Zachman). Background in software engineering, data architecture, or infrastructure engineering. Exposure to designing internal accelerators, frameworks, or reusable components. Awareness of AI/ML architecture patterns, generative AI integration considerations, or data lineage and monitoring concepts. Company Rapidly growing financial services organisation with offices in London Hybrid working Salary ...

lifecycle.Drive architectural governance, ensuring traceability, documentation accuracy, and compliance.Ensure solutions meet compliance standards (e.g. ISO 27001).AI & Data AwarenessEnsure solution designs support AI/ML-enabled capabilities where relevant (e.g. data lineage, governance, feature management, and model integration patterns).Collaborate with wider technical teams to define integration approaches for predictive … frameworks (e.g. TOGAF, Zachman).Background in software engineering, data architecture, or infrastructure engineering.Exposure to designing internal accelerators, frameworks, or reusable components.Awareness of AI/ML architecture patterns, generative AI integration considerations, or data lineage and monitoring concepts.CompanyRapidly growing financial services organisation with offices in LondonHybrid working Salary & BenefitsThe salary range ...

tech lead or staff engineer at a SaaS or enterprise software vendor with a forward-deployed or professional services motion.Experience with AI/ML platform deployments or data-heavy enterprise applications at scale.Familiarity with major cloud environments: AWS, Azure, or GCP, including managed ML/AI services.Experience in regulated industries ...

including payments, GL postings, month-end processes, master/reference data updates, batch orchestration and downstream reporting. Drive innovation in testing using AI/ML techniques, performance engineering, observability, service resilience validation and data quality analytics. Elevate engineering maturity through shift-left and shift-right testing, reusable automation frameworks, quality … Test Manager or equivalent quality leadership certification. ITIL v3/v4 Foundation or experience aligning QA with service management practices. Experience applying AI/ML in Quality Engineering, including test optimisation, defect prediction, anomaly detection or analytics-led assurance. Experience with enterprise orchestration tools such as Control-M, Autosys ...

shipped product.Your core focus is on building and shipping AI-powered features, with a strong collaborative element across Product Engineering, AI Platform, and Data & ML Platform teams.What you’ll be doingAs a Staff Applied AI Engineer you will:Build and ship multiple AI-powered product features, setting … APIs.Experience building APIs, services and data retrieval pipelines (RAG, vector search etc) to feed data into LLMs.Deep proficiency with Python for both data and ML engineering, SQL and major cloud providers.An extensive background in traditional ML engineering and a deep understanding of how to architect and build data systems ...

agile team that designs, builds, and operates the services that make large language models usable at scale. This is an infrastructure-meets-ML role: you don't need to be an ML researcher, but you should be excited to learn how model architectures and inference constraints translate into real production ...

operations (predictive monitoring, anomaly detection, auto-remediation).Implement automation for repetitive BASIS operations (system health checks, patching, job management).Leverage AI/ML tools for incident prediction, root cause analysis (RCA), and performance optimization.Introduce intelligent monitoring dashboards and self-healing mechanisms across SAP landscape.Enable integration of SAP operations with enterprise … transfer, and training to internal teams and stakeholders.Good to have:Strong understanding of ITIL-based Service Delivery and Service Management practices.Knowledge of AI/ML-based monitoring or AIOps tools for enterprise platforms.Experience with SAP ALM tools (Solution Manager, Focused Run, Cloud ALM).Exposure to SAP Rise, GTS, Ariba ...