301 to 325 of 4,924 Machine Learning Jobs in England

Impact you will have Architecting Workloads: Design and implement production-level ML and AI workloads, including end-to-end pipelines, training/inference optimization, MLOps lifecycle management, and integration with cloud-native services. GenAI Leadership: Serve as a practitioner for enterprise GenAI solutions, specializing in RAG architectures, agentic systems (including … well as by presenting at industry conferences and leading hackathons. What we look for Experience: 10+ years of hands-on industry DS/ML experience, with a focus on either: ML Engineering: Building/maintaining production-grade cloud infrastructure (AWS/Azure/GCP) that supports deployment of ML applications ...

GDPR, data privacy, and information security Awareness of data models in a Medalion Architecture Experience building Semantic, Metric or Analytic models Experience of building Machine Learning models Any experience in MLOps or operationalising Machine Learning Knowledge of Data Quality Frameworks in Python Qualifications: Industry focused degree ...

GDPR, data privacy, and information security Awareness of data models in a Medalion Architecture Experience building Semantic, Metric or Analytic models Experience of building Machine Learning models Any experience in MLOps or operationalising Machine Learning Knowledge of Data Quality Frameworks in Python Qualifications: Industry focused degree ...

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 ...

manage their data with efficiency and ease. You will work closely with people from a wide variety of domains: Product Data Scientists, Analytics Engineers, ML Engineers, MLOps, MarTech and other Data Engineering teams. You will help manage our growing data needs and support increasingly complex business problems by building … securely, using modern tooling such as Kafka, Terraform, Docker, and cloud‐native patterns Lead technical initiatives: Lead initiatives working with end users: data scientists, ML engineers, analytics engineers, product engineers and beyond to enable, support and accelerate their data needs, embracing a platform as product mindset Uphold operational excellence: building ...

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 ...

identifying risks and opportunities for improvement Champion engineering excellence across code quality, testing, continuous delivery, security, observability and platform reliability Collaborate closely with AI, Machine Learning, Product, Infrastructure and DevOps teams to deliver integrated platform capabilities and share knowledge across the engineering organisation We tend to look … systems integrators Strong communication and collaboration skills, with the ability to influence technical decisions across teams Experience building or contributing to AI and Machine Learning platforms Experience integrating large language models, speech technologies or multimodal AI solutions into production environments Familiarity with AI orchestration frameworks, intelligent workflows ...

including asset managers, pension funds, hedge funds, and sovereign wealth funds. The successful candidate will bring a unique blend of equity research, quantitative modelling, machine learning, and platform development expertise, with the ability to translate complex datasets into differentiated investment insights while driving innovation across the research process. … equity market structure and investment processes, with expertise in cross-sectional and time-series modelling, factor research, and the application of statistical and machine learning techniques to investment research and alpha generation. Communication & Intellectual Curiosity Excellent written and verbal communication skills, with the ability to communicate sophisticated quantitative ...

prior experience on Oracle applications, with focus on designing and implementing AI solutions based on Oracle. Proven experience delivering data platform, analytics, AI or machine learning projects using Oracle technologies. Strong technical experience across Oracle Cloud Infrastructure (OCI), Oracle Autonomous Database, Oracle Database, Oracle Data Integration, GoldenGate, Oracle … Autonomous Database Oracle Data Integration Oracle GoldenGate Oracle Analytics Cloud (OAC) Oracle Data Intelligence OCI Data Science OCI AI Services OCI Generative AI Oracle Machine Learning (OML) Oracle Vector Search Oracle Exadata OCI Landing Zone Oracle Integration Cloud (OIC) #J-18808-Ljbffr ...

output of our rail inspection systems. You will work across the full stack with a strong emphasis on backend data processing, analytics, and machine learning workflows, all hosted on AWS cloud infrastructure. These seats sit close to the ranking and fusion logic itself, so the work … serve data products to internal and external consumers Work with large-scale rail inspection datasets including ultrasonic, electromagnetic, and operational data Implement and deploy machine learning models and statistical analyses in production environments Architect and manage AWS cloud infrastructure for data workloads (S3, Lambda, Glue, Athena, SageMaker, Step ...

Platform working against their real data and workloads, not slideware. Meet technical buyers on their own ground across modern data engineering (Spark, Delta, streaming), machine learning, and Generative AI, and integrate cleanly with their existing cloud and open-source stack. Move at start-up speed: qualify quickly, prove … Java, and a willingness to learn (or existing knowledge of) Spark. Familiarity with a core data or AI domain: modern data engineering, streaming, machine learning, or Generative AI (e.g. RAG, fine-tuning, LLMOps). Experience with the modern data stack and open-source data tooling, and with ...

marketplace efficiency, partner ROI, and revenue growth Own ad relevance initiatives that enhance the quality and personalization of sponsored listings for travelers Partner with machine learning and engineering teams to design, implement and optimise auction algorithms that balance traveler experience, partner value, and business objectives Define success metrics … digital advertising, marketplace platforms, or auction-based systems Proven track record of launching and scaling technical products that drive meaningful business outcomes Experience with machine learning applications, preferably in advertising or marketplace optimization Strong analytical skills with experience using data to inform product decisions and measure success Proficient ...

Lead the design and evolution of the cybersecurity analytics architecture, defining data patterns, modelling approaches and data product frameworks that support reporting, advanced analytics, machine learning, GenAI and AI-powered analytics experiences at scale. Data Integration, Transformation and Quality: Establish the strategic approach for data integration, transformation … Cyber Analytics team. You will need Strong passion for data engineering, data modelling, data quality and building trusted, scalable data products that enable analytics, machine learning and AI-driven use cases. Proven experience leading the design and delivery of enterprise-scale data products, defining technical strategy, architectural patterns ...

automationPrompt engineering, AI evaluation and Responsible AIAI orchestration frameworks e.g. LangChain, Semantic Kernel, Model Context Protocol (MCP)Data engineering, pipelines, modelling and governanceAdvanced analytics, machine learning and statistical modellingData visualisation and insight solutionsCandidates should understand the importance of trusted, accessible and AI-ready data, and be curious about … into business processes and decision-making.Technical Skills:Hands-on experience in one or more of the following areas:Programming & Analytics – Python, SQL, R, Spark, machine learning and advanced analyticsCloud & Data Platforms – Microsoft Fabric, Databricks, Snowflake, Azure, AWS and GCPAI Technologies – GenAI frameworks, Agentic AI, vector databases, semantic search ...

prior experience on Oracle applications, with focus on designing and implementing AI solutions based on Oracle. Proven experience delivering data platform, analytics, AI or machine learning projects using Oracle technologies. Strong technical experience across Oracle Cloud Infrastructure (OCI), Oracle Autonomous Database, Oracle Database, Oracle Data Integration, GoldenGate, Oracle … Autonomous Database Oracle Data Integration Oracle GoldenGate Oracle Analytics Cloud (OAC) Oracle Data Intelligence OCI Data Science OCI AI Services OCI Generative AI Oracle Machine Learning (OML) Oracle Vector Search Oracle Exadata OCI Landing Zone Oracle Integration Cloud (OIC) About Accenture Accenture is a leading global professional services ...

high-ownership role working centrally across the business. You'll partner with teams spanning Commercial, Marketing, Product, Finance, Engineering and Operations — developing and deploying ML and AI solutions that drive outcomes across both sides of our marketplace. The problems you'll work on are genuinely varied: pricing models, propensity … deliver them end-to-end, from first principles through to being deployment-ready and beyond. WHAT YOU'LL BE DOING End-to-End ML & AI Delivery: Lead data science initiatives from problem framing through to deployment, monitoring, and iteration — delivering the full production lifecycle. With no dedicated ML engineering function ...

About Signal Ocean Signal Ocean is the technology arm of the Signal Group, providing market-leading advanced machine learning and AI-driven intelligence to shipping and commodities professionals worldwide. Our platform delivers tailored, exclusive insights through web, mobile, and API interfaces, enabling clients to make faster, better-informed … while diving deep into our products and/or the shipping world. Career growth opportunities and a structured development discussion every 4 months. Personal learning budget for training, seminars, conferences (750 to 2000 EUR annually depending on seniority). Regular team bonding events and activities. Fitness benefits to support ...

looking for a Machine Learning Engineer to shape and scale their pricing technology. In this role, you'll design and own ML platforms that streamline pricing workflows, support rapid model deployment, and ensure models perform reliably at scale. Partnering with Data Science, Actuarial, and Product teams. Responsibilities: Build … support ML lifecycle tooling for model deployment, monitoring, and alerting Maintain and improve the Kubeflow environment for Data Scientists and Actuaries Create pricing analytics tools to accelerate impact analysis and reduce manual work Collaborate with pricing and product teams to deliver high-impact tooling Communicate complex concepts clearly to technical ...

governance, security, privacy, lineage and quality, and how these are embedded into architecture and delivery. An understanding of the data requirements of AI and machine‐learning applications, including securely making structured and unstructured enterprise data available to AI solutions. A good understanding of modern software engineering and SDLC … architectural decisions and trade‐offs to technical and non‐technical colleagues. Desirable experience Architecting applications or platforms incorporating generative AI, large language models or machine learning. Designing data and integration architectures for AI applications, including retrieval and grounding approaches. Building internal developer platforms, shared services or reusable application frameworks. ...

e.g., GitHub Copilot, generative AI coding assistants) to improve engineering productivity, code quality, and delivery efficiency Understanding of data engineering considerations for AI and machine learning workloads, including data quality, governance, lineage, and scalability requirements Education Bachelor’s degree or equivalet experience; Master’s degree is a plus ...

reuse. Help reduce one-off security consultations by embedding approved security decisions into tooling, templates, and standard delivery workflows. Requirements : Essential - Experience in machine learning engineering. Strong experience in cloud security engineering, application security, security architecture, DevSecOps, or security automation. Hands-on experience with at least one major … Dental Insurance Maternity, paternity, and shared parental leave Employee Assistance Programme Access to employee resource groups with dedicated time to volunteer. Access to extensive learning and development resources Access to employee discounts scheme via Perks at Work About the business- LexisNexis Intellectual Property Solutions (LNIP) is the global leader ...

system analysis, recommending changes, and integrating new policies, procedures, and technologies. Stay current with emerging tools, programming techniques, and industry best practices through continuous learning, professional engagement, and adoption of modern technologies (including open source). Ensure quality and reliability by actively participating in testing, validation, and certification processes … successful in this role you will need the following: Technical Expertise: Proven experience with cloud-based systems and architectures (Azure, AWS, IoT, AI/ML), DevOps practices, CI/CD pipelines, RDBMS (MS SQL, Oracle, PostgreSQL), and integration technologies (APIs, REST, SOAP, webhooks). Proficient in an enterprise language such ...

Fabric Data Factory, Data Factory CDC, Fabric/Synapse Spark, ADF, Synapse Pipelines, Fabric, dbt Data management & metadata: Purview AI: Foundry, (including Agent Service), ML Data Product mentality : You build Data Products where every pipeline and dataset is discoverable, addressable and secure by design. Data capabilities : You know the full … real value You’re comfortable with ambiguity and solving complex problems collaboratively You bring strong expertise in your craft, alongside a willingness to keep learning You communicate clearly and build trust fast with clients, data engineering leaders and data and software engineers You’re pragmatic, adaptable, outcome‐focused ...

formal management authority.* Clear communication skills and experience working across engineering, data science, security, architecture, and product teams.## Bonus points* Experience with AI or machine learning platforms, model-serving infrastructure, MLOps, or data-intensive services.* Knowledge of advanced networking, API management, distributed systems, service mesh, or zero-trust … teams:** We bring together software engineers, data scientists, security specialists, product partners, and technical leaders to deliver dependable systems.**Continued development:** We support continuous learning, deeper technical specialization, and broader architectural responsibility.## Equal opportunity and reasonable accommodationsWe are committed to equal opportunity and an inclusive recruitment process. We welcome ...

catalyst for accountable growth, not a brake. What We Are Looking For Engineering & Technical Leadership Substantial experience leading software engineering, data, or AI/ML teams, typically 12+ years of relevant experience with several in a leadership capacity, delivering production-grade solutions at enterprise scale. Strong hands‐on foundations … example Python, SQL, cloud‐native platforms, data pipelines), enough to set technical direction credibly and make sound architecture decisions. Demonstrated experience with AI/ML technologies, including LLMs, Retrieval Augmented Generation (RAG), agentic workflows, Natural Language Processing (NLP), and predictive analytics, and the discipline to run them reliably in production. ...