1,401 to 1,425 of 1,721 Machine Learning Jobs in England

fastest growing talent markets in the world - and we're looking for our next ambitious hire. We place Forward Deployed Engineers, AI/ML Engineers, Founding Engineers and senior technical talent across the US, UK and Europe. Our clients are AI-native startups, boutique consultancies and frontier tech businesses. This ...

business functions. Strong analytical and problem-solving skills with a pragmatic approach to risk management. Desirable: CIPM certification. CIPT qualification. Experience with AI/ML governance frameworks, NIST AI Risk Management Framework, or equivalent AI governance standards. Got your attention? If you believe that you have the skills and experience ...

tions.Strong analytical and problem-solving skills with a pragmatic approach to risk manag ement. Des irable:CIPM certifi cation.CIPT qualifi cation.Experience with AI/ML governance frameworks, NIST AI Risk Management Framework, or equivalent AI governance sta ndards. ...

talent as the team grows. Ideal candidate credentials Proven sales leadership experience building and managing sales teams in high-growth SaaS or AI/ML-centric software companies. Deep understanding of the EMEA market with proven ability to grow business in the region. Track record of meeting/exceeding revenue ...

Software Roots: A strong foundational background in embedded software is required, alongside the technical breadth to converse fluently across DSP, FPGA, and AI/ML domains. Proven Formal Management: Direct experience acting as a formal line manager for a team, handling appraisals and performance development. Experience managing other managers ...

bids and business development activities ensuring that proposed solutions are feasible, innovative, compliant, and mission‐aligned Working closely with engineering, data, cyber, AI/ML, and systems integration teams to shape end‐to‐end solutions Translating complex missions’ needs into robust technical architecture, capability concepts, and delivery approaches Technically lead ...

PROFILE We’d love to meet someone with: Proven experience leading complex data science, Agentic & Generative AI, and analytics projects, delivering value across the ML lifecycle using strong foundations in statistical modelling, natural language processing, time-series analysis, spatial analytics, and mathematical modelling methodologies. Experience managing the delivery … able to build and maintain stakeholder relationships and influence effectively within a matrixed consulting environment. The ability to apply domain expertise and AI/ML innovation to solve client challenges, and present clear, compelling insights to diverse audiences. A proactive approach to business growth - identifying opportunities, contributing to proposals ...

lead a transformation mandate: move a legacy, on-prem supply chain platform to a cloud-native, composable SaaS architecture and embed AI/ML and generative AI across the product suite. The role is based in EMEA (Paris headquarters) and includes global engineering leadership and client-facing responsibilities. Key Responsibilities … analytics). Architect transformation from monolithic legacy systems to composable, API-first, cloud-native SaaS using microservices and event-driven design. Embed AI/ML as a foundational design principle and integrate generative AI/LLMs for copilots, natural language interfaces, autonomous workflows, and agentic capabilities. Own technical due diligence ...

that enhances governance, operations, and investment on a global scale. At Quantios, we are committed to fostering a diverse and inclusive workplace where creativity, learning, and collaboration drive success. As a Data Architect at Quantios, you will be responsible for designing the enterprise data architecture underpinning Quantios Insights … governance tools (Purview, Unity Catalog, Snowflake Governance, Fabric Governance). Experience designing data platforms to support analytics, BI, operational reporting, and AI/ML workloads. Understanding of LLM/RAG data preparation, unstructured data processing, and vectorisation workflows is advantageous. Strong communication skills with the ability to collaborate with engineering ...

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 ...

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 ...

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 ...

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 ...

enterprise data strategy. The ideal candidate will partner with business and technology leaders to deliver high-performance data systems that support analytics, AI/ML, and real-time insights. Key Responsibilities Architecture & Solution Design Architect end-to-end Databricks Lakehouse solutions including data ingestion, ETL/ELT pipelines, Delta Lake … Proven experience leading teams and delivering enterprise-grade data solutions. Preferred Qualifications Databricks certifications (e.g., Databricks Certified Data Engineer Professional, Architect ). Experience building ML solutions using MLflow or integrating with cloud ML services. Experience in BFSI, Retail, Telecom, or Healthcare data environments. Experience with real-time data processing (Kafka ...

development Exposure to tooling such as Terraform, APIs, or CI/CD pipelines (desirable) Experience working in Business Intelligence/analytics environments AI/ML Exposure (Essential) Candidates must demonstrate practical exposure to AI/ML, such as: Working with cloud-based AI services (e.g. AWS Bedrock or similar) Supporting … enabled data products or workflows Understanding generative AI concepts, including prompt engineering Exposure to ML pipelines or collaboration with Data Science teams (This does not need to be a core specialism but must be clearly evidenced.) Experience Required Typically 4-8+ years' experience in data engineering/BI roles ...

intersection of three businesses: (1) a private equity investment arm, (2) an in-house AI transformation firm that designs and deploys bespoke GenAI, ML, and automation solutions, and (3) a suite of proprietary software products. Our team comes from places like Google, Palantir, Meta, Surge AI, Blackstone, TPG, Cerberus, Millenium … end. About You: You are a hybrid: part technologist, part strategist, part operator. You are equally comfortable whiteboarding a model architecture with an ML engineer, presenting an AI transformation roadmap to a private equity partner, and pressure-testing an LBO model. You move fast, you think in structures ...

autonomous, multi-step AI reasoning and execution within enterprise applications. End-to-End AI Delivery: Drive the full lifecycle development of complex AI/ML systems, building on a track record of successfully bringing production-grade AI solutions to market. Software Engineering & Architecture Production-Grade Python Coding: Write, test … complex technical challenges, applying deep debugging expertise to resolve system issues efficiently. Leadership & Team Collaboration Technical Leadership: Lead, direct, and mentor AI/ML engineering teams, setting quality standards and fostering a culture of technical excellence. Project Delivery: Oversee technical project execution, ensuring milestones are met on time and within ...

enterprise customers navigating complex analytics modernisation challenges whether migrating from legacy on-premises data warehouses, building unified data platforms, implementing streaming analytics, or operationalising ML-ready data foundations. You'll translate ambiguous business requirements into scalable, cost-effective analytics architectures that accelerate time-to-insight. You will join a team … provide customer feedback to analytics product teams, participate in private betas, and shape future service capabilities Collaborate across specialist teams work with AI/ML, Security, and Migration specialists to connect analytics foundations to downstream ML and GenAI workloads About the team We're the AWS Analytics Specialist Solutions Architecture ...

enterprise customers navigating complex analytics modernisation challenges whether migrating from legacy on-premises data warehouses, building unified data platforms, implementing streaming analytics, or operationalising ML-ready data foundations. You'll translate ambiguous business requirements into scalable, cost-effective analytics architectures that accelerate time-to-insight. You will join a team … provide customer feedback to analytics product teams, participate in private betas, and shape future service capabilities Collaborate across specialist teams work with AI/ML, Security, and Migration specialists to connect analytics foundations to downstream ML and GenAI workloads About the team We're the AWS Analytics Specialist Solutions Architecture ...

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 ...

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 ...

client pitch contribution, client hosting at events. Internal Contribution – Campaign development, internal think-tanks, whitepapers, practice development (operations, recruitment, team events & activities), offering development. Learning & Development – Training to support your career development and the skills demand within the company, certifications etc. Your Profile Our ideal candidate will bring … other similar. Experience in working within the fields of Data Science and Analytics, with a proven track record of successfully delivered work across the ML lifecycle. Experience with Large Language Models architectures and techniques: AI-agents, GraphRAGs, fine-tuning, semantic grounding. A desire to provide solutions to the real-world ...