1,026 to 1,050 of 1,236 Machine Learning Jobs in England

integrated technical blueprints covering AI, analytics, applications, integration, and security. Define and communicate the digital and data architecture vision - including use of generative AI, ML platforms, and automation accelerators. Balance innovation with cost efficiency, delivery feasibility, and risk. User-Centric Problem Solving - Solutions must be designed with end-user productivity … experience: Digital Architecture 10+ years designing large-scale digital transformation solutions - including AI, data platforms, and cloud architectures. AI & Data Expertise in AI/ML platforms (Azure AI, AWS SageMaker, Google Vertex AI), data governance, analytics, and responsible AI practices. Cloud & Integration Strong understanding of hybrid and multi-cloud architectures ...

execution across complex migrations, AI enablement, and digital modernisation. Architect and deliver agentic AI systems (LangGraph, LangChain, tool-calling, memory), RAG pipelines, and enterprise ML workloads. Skilled in Azure and AWS AI stacks, Fast API microservices, Kubernetes, and secure vector search patterns. Strong background in FinOps, secure landing zones … contributor to AI leadership content, events and thought leadership, simplifying frontier AI for executive audiences. Core Capabilities Enterprise AI & Architecture Agentic AI, RAG, enterprise ML in regulated FS Azure AI Studio, Azure AI Search, Fabric, Document Intelligence AWS Bedrock & SageMaker pattern experience FastAPI, Kubernetes, Docker, CI/CD (ADO/ ...

dedicated team is responsible for overseeing data use, governance, and controls around the build, adoption and maintenance of cloud infrastructure, data and AI/ML products. With a focus on both effectiveness and responsibility, we strive to push the boundaries of innovation while ensuring ethical and sustainable practices. Join … focuses on developing scalable LLM-based products and reusable back-end APIs. You will engage in close collaboration with cross-functional teams, including the ML Centre of Excellence, AI Research, Cloud Engineering, and others, to foster innovation and deliver solutions that yield a high Return-on-Investment (RoI). ...

advanced AI systems that deliver real business impact. Responsibilities as a Principal AI Engineer: Lead end‐to‐end delivery of scalable, resilient AI/ML pipelines aligned to business goals. Build and deploy advanced ML, DL, and LLM solutions, including RAG, agentic architectures, and evaluation frameworks. Mentor engineers in ML ...

working with one of the UK's fastest-growing, well-funded tech start-ups, is hiring Multiple Data Engineers/Data Scientists/ML Analysts to join our cutting-edge team in London. We're on a mission to scale rapidly – with plans to grow by 40 heads this year ...

PowerBI, Tableau, Looker,... Background in Data Governance and Data Catalog solutions: Axon, Informatica EDC, Colibra, Purview, etc. Previous experience in Artificial Intelligence techniques: ML/Deep Learning, Computer Vision, NLP, etc General information: Start Date: ASAP Length of Contract: 1 year (minimum) Work Location: Madrid Remote working. ...

best practices for “global-by-default” development. Participate in quarterly planning & prioritization cycles and drives execution of assigned globalization initiatives. 2. AI/ML enablement Build integrations between LLMs, MT engines, and internal systems using APIs. Run technical experiments to test new AI-powered workflows, notably using Agentic AI. Engineer … reports from MT and TMS data sources. Partner with linguists and vendors to operationalize technical improvements. 4. Cross-functional delivery Collaborate with Product, UX, ML, and Platform teams to embed globalization early in the development lifecycle. Support workflow automation and process improvements. Help define success metrics and track business impact. ...

time Job Shift Day Job Description The Chief Data and Analytics Office (CDAO) builds enterprise-scale platforms for Data Management, Analytics, and AI/ML Operations used firm-wide across JPMorgan Chase. Within CDAO, the Data for AI Product Management team creates reusable platform solutions that transform how data producers … What You'll Do Own the Catalog Vision & Strategy Define the multi-year product vision and roadmap for firmwide data discovery serving data scientists, ML engineers, analytics engineers, and increasingly business users. Establish north-star metrics tied to real impact: time-to-data, publishing velocity, discovery-to-integration conversion, repeat ...

pipelines at scale Background in operations research or supply chain optimisation Exposure to LLMs as signal sources — extracting structured market intelligence from unstructured text ML Skills We're Looking For This role sits at the intersection of classical econometrics and modern machine learning. You don't need … outperform neural approaches on structured data, and vice versa. Strong intuition for regularisation, hyperparameter tuning, and avoiding leakage in time series cross-validation. Deep Learning for Sequences. Hands-on experience with temporal architectures - LSTMs, GRUs, Temporal Fusion Transformers, N-BEATS, or similar. Understanding of attention mechanisms and when transformer ...

experience across all Identity and Access Management core disciples including identity management, identity governance and administration, privileged access, and conditional access and in particular, machine identities. It also requires deep technical skills in the DevSecOps. This role will support the transformation of IAM into a modern, automated, predictable … SDLC from the ground up, ensuring AI models and systems are secure by default. Define and enforce secure coding practices for AI/ML components and APIs. Identify and assess threats specific to AI systems, such as model inversion, data poisoning, adversarial attacks, and model theft. Implement model encryption ...

What We’re Looking For Strong experience as an AI/ML Engineer or Applied ML Engineer Deep hands-on knowledge of Google Cloud Platform (Vertex AI, BigQuery, Cloud Run, GKE, Pub/Sub) Proven track record building LLM, GenAI, or traditional ML solutions end-to-end Comfortable in startup … scale-up environments — fast-moving, iterative, delivery-focused Strong Python engineering experience Experience with MLOps, CI/CD, IaC, and productionising ML models Ability to work collaboratively with product, data, and engineering teams Contract Details Location: Hybrid London (2–3 days onsite) Start Date: ASAP Length: 6 months rolling ...

optimisation, and observability Architect and implement multi-cloud, data lake, and data warehouse platforms Design scalable data pipelines, integration workflows, and analytics solutions Apply ML/AI frameworks, semantic models, and BI/visualisation tools to solve client challenges Operate as a strategic and technical leader across client engagements, guiding … Azure, GCP) and data technologies such as Snowflake, Databricks, or equivalent Experience with programming/scripting, data integration, ETL pipelines, and orchestration Knowledge of ML/AI frameworks, BI/analytics platforms, and semantic data modelling Strong client-facing skills with the ability to translate business needs into technical solutions ...

optimisation, and observability Architect and implement multi-cloud, data lake, and data warehouse platforms Design scalable data pipelines, integration workflows, and analytics solutions Apply ML/AI frameworks, semantic models, and BI/visualisation tools to solve client challenges Operate as a strategic and technical leader across client engagements, guiding … Azure, GCP) and data technologies such as Snowflake, Databricks, or equivalent Experience with programming/scripting, data integration, ETL pipelines, and orchestration Knowledge of ML/AI frameworks, BI/analytics platforms, and semantic data modelling Strong client-facing skills with the ability to translate business needs into technical solutions ...

optimisation, and observability Architect and implement multi-cloud, data lake, and data warehouse platforms Design scalable data pipelines, integration workflows, and analytics solutions Apply ML/AI frameworks, semantic models, and BI/visualisation tools to solve client challenges Operate as a strategic and technical leader across client engagements, guiding … Azure, GCP) and data technologies such as Snowflake, Databricks, or equivalent Experience with programming/scripting, data integration, ETL pipelines, and orchestration Knowledge of ML/AI frameworks, BI/analytics platforms, and semantic data modelling Strong client-facing skills with the ability to translate business needs into technical solutions ...

Role: AI/ML Computational Science Manager Location: London Salary: Competitive salary and package dependent on experience Career Level: Manager (CL7) Accenture is a leading global professional services company, providing a broad range of services in strategy and consulting, interactive, technology and operations, with digital capabilities across all of these … industries, including Financial Services, Resources, Products, Communications and Health & Public Services. In our team, you will: How to help clients to use AI/ML technologies to solve business challenges How to design, develop, deploy, and run high quality AI/ML solutions across a range of industries with varying ...

dashboards—you'll be responsible for your own analytics and program measurement A deep understanding of the startup ecosystem and AI/ML technology landscape—can speak credibly about technical products to technical audiences Built relationships with VCs, worked at a VC firm, or successfully partnered with accelerators to drive … experience working for or with venture capital firms Technical background—former developer, PM with hands‐on coding experience, or deep familiarity with AI/ML development workflows Developer advocate or developer relations background with active presence in technical communities Familiarity with large language models and their applications in generative ...

Head of Data & Analytics, you will design, develop and maintain secure, high-quality data pipelines that enable trusted reporting, analytics, and future AI/ML development. This is a rare opportunity to influence architecture, engineering standards, automation and governance within a co-managed delivery model. You will work across structured … including: 34 days annual leave (including public holidays) Access to earned pay before payday Company pension scheme Generous occupational maternity/paternity pay Ongoing learning and development opportunities Health Cash Plan after probation (covering dental, optical, therapies, maternity/paternity, prescriptions and more) Opportunities for career progression ...

quickly together, embracing collaboration and change as part of start-up life.? Individuals thrive here if they enjoy taking ownership, wearing multiple hats and learning quickly, and are comfortable going beyond core hours when work demands it - not because it is expected every day, but because seeing progress matters. … Integrate performance testing techniques across multiple types of simulation (e.g. Gazebo, rosbag-based workflows).? Collaborate with hardware engineers, systems architects and AI/ML specialists to integrate embedded software and test frameworks into the overall system.? Participate in code reviews, performance optimisation and comprehensive testing (unit, integration and system ...

based on user feedback Strong problem-solving skills and ability to work independently with minimal supervision Nice-to-have Bonus: Experience with AI/ML systems, LLMs, or working in regulated industries (fintech, compliance, etc.) Bonus: Experience with high-scalable AWS architecture Our tech stack NodeJS/Typescript NextJS Python … actively, embrace feedback and foster a collaborative environment where ideas are shared openly. You are confident in your expertise while recognising the value of learning from others and adapting to change. Budget: Base salary £60k-£90k Equity: 0.5-1.0% Negotiable, depending on preferences The interview process ⏳ We are seeking ...

Knowledge of IAM design, network security controls, encryption, secrets management, and cloud identity principles. Understanding of modern cloud architectures (serverless, microservices, managed AI/ML services) and their associated security risks. Ability to collaborate effectively with AI engineers, developers, and cloud teams to ensure secure implementation of AI workloads. Desirable … vector databases, model APIs, or data pipelines used by LLMs. Knowledge of responsible AI principles, model governance, or AI-specific threat modelling (e.g., adversarial ML, data poisoning, prompt injection). Background working in regulated industries such as Financial Services or Insurance. Strong stakeholder communication skills, including the ability to influence ...

Knowledge of IAM design, network security controls, encryption, secrets management, and cloud identity principles. Understanding of modern cloud architectures (serverless, microservices, managed AI/ML services) and their associated security risks. Ability to collaborate effectively with AI engineers, developers, and cloud teams to ensure secure implementation of AI workloads. Desirable … vector databases, model APIs, or data pipelines used by LLMs. Knowledge of responsible AI principles, model governance, or AI-specific threat modelling (e.g., adversarial ML, data poisoning, prompt injection). Background working in regulated industries such as Financial Services or Insurance. Strong stakeholder communication skills, including the ability to influence ...

Knowledge of IAM design, network security controls, encryption, secrets management, and cloud identity principles. Understanding of modern cloud architectures (serverless, microservices, managed AI/ML services) and their associated security risks. Ability to collaborate effectively with AI engineers, developers, and cloud teams to ensure secure implementation of AI workloads. Desirable … vector databases, model APIs, or data pipelines used by LLMs. Knowledge of responsible AI principles, model governance, or AI-specific threat modelling (e.g., adversarial ML, data poisoning, prompt injection). xkybehq Background working in regulated industries such as Financial Services or Insurance. Strong stakeholder communication skills, including the ability ...

from the ground up. What you'll own: Build end-to-end product features across the full stack (frontend, backend, infra) Integrate AI/ML capabilities — risk stratification, smart triage, personalisation Build privacy-first, regulatory-compliant infrastructure (UK GDPR, NHS DSPT, MHRA) Shape and evolve the architecture and technical foundations … stage product teams: you've shipped and scaled full stack products Strong backend (Node.js, Python/Flask, FastAPI) and frontend (React, Next.js, Vue) fundamentals ML/data science proficiency: Python, SQL, pandas, scikit-learn, PyTorch/TensorFlow Experience with cloud platforms (AWS, GCP, Azure) and containerisation (Docker, Kubernetes) Proven ability ...

Identify performance or reliability bottlenecks and propose improvements. Required Qualifications & Experience Strong experience with Python and Django. Familiarity with Torch (PyTorch) for analytical or ML workloads. Proficiency in SGLang or willingness to learn domain-specific languages. A keen sense of system design and desire to build elegant, maintainable solutions. General … time streaming architectures. Familiarity with cloud platforms (AWS, GCP, Azure) and container orchestration (Kubernetes/Docker). Exposure to data pipelines, analytics workflows, or ML deployment. Experience working in startup or product-led teams. Why Zuma Labs? Work in a high-impact startup environment where your work immediately affects ...

schema validation, completeness, freshness, thresholds, and automated alerting. Enhance end-to-end pipeline resilience, monitoring, observability, failure handling, and recovery mechanisms. Integrate AI/ML features to boost reliability, anomaly detection, and operational efficiency. Collaborate closely with Data Product teams, Analytics Engineering, and Data Science to deliver production-grade data … expectations. Preferred Experience: Exposure to AI-enabled pipeline capabilities, such as anomaly detection or intelligent monitoring. Good understanding of MLOps or supporting deployment of ML models into production environments. Experience with CI/CD automation, testing frameworks, and observability tooling. Contracting Route: Timesheets via Umbrella Company This is an exceptional ...