151 to 175 of 4,798 Machine Learning Jobs in England

passionate about leveraging technology to make a difference. Discover how you can shape the future of financial services with us. As an Applied AI & ML Scientist in the Market Operations team, you will design, develop, and deploy AI/ML solutions that directly support and enhance Markets Operations. You will … efficiency across the team. Job Responsibilities: Develop and implement advanced machine learning models and algorithms to address operational challenges Deploy AI/ML solutions for process automation, anomaly detection, document intelligence, and workflow optimization Architect and oversee generative AI applications to automate and enhance business processes Build ...

Senior AI/ML Engineer ££90,000 - £110,000 GBP No Hybrid WORKING Location: UK wide , Central London, Greater London - United Kingdom Type: Permanent Senior AI Engineer - London (Remote) We're looking for an experienced AI Engineers to lead the next generation of AI-powered learning experiences. … strategy, architecting scalable solutions, and bringing innovative products to millions of learners. This is an opportunity to join a fast-growing online learning platform where your work will directly influence how people develop new skills, advance their careers, and achieve their goals. The Role As an AI Engineer ...

innovation in this fast evolving space as new technologies reshape how money moves. In this role, you will work at the forefront of modern machine learning and generative AI to deliver meaningful, lasting impact on global finance. You will partner closely with product, operations, risk, and technology teams … measurable outcomes. You will also have opportunities to mentor others and help shape how we build and operate production AI. As a Vice President Machine Learning Data Scientist in Payments Machine Learning, you will lead the design, development, and production deployment of machine learning ...

About the role The AI & ML Engineering team accelerates the adoption of AI across the business, championing innovation while ensuring our machine learning solutions are robust, scalable, and cost-efficient. We enable teams to solve problems using existing AI tools where possible and build custom solutions when needed. … remit spans AI enablement, agentic systems development, and “conventional” ML engineering for non-GenAI applications e.g. recommender systems, forecasting models, and more. We’re looking for an AI & ML Engineer who is passionate about building production‐ready AI and machine learning solutions. You'll work across a variety ...

here. Everything that makes you unique is welcome; join us and let’s build what’s next - together! Role Overview We are seeking a ML Ops Technical Lead to spearhead our infrastructure, cost-optimisation, and deployment strategies. You will manage a talented team of DevOps engineers while remaining deeply technical … hands-on. Your primary mission is to build, scale, and secure the foundational platforms for our machine learning (ML) and generative AI (GenAI) models while maintaining financial accountability. Your Impact Team Leadership & Collaboration: Lead and manage a dedicated DevOps team, mentoring both junior and senior engineers while collaborating ...

experiences worldwide. Задачи: Design and implement agentic systems using RAG, grounding, prompt engineering, and orchestration on a GCP-first stack; Build and maintain production ML pipelines and services for recommender systems, customer segmentation, marketing optimisation, and other non-GenAI use cases; Develop secure, scalable, and observable APIs and microservices …/ML solutions; Implement CI/CD for ML services and infrastructure as code; Monitor model and data drift and performance; Establish guardrails for safe AI usage, including prompt security, evaluation frameworks, and privacy compliance; Contribute reusable components, documentation, and engineering best practices; Collaborate with data engineers, data scientists, front ...

MLOps Engineer to join our Data & Compute Platform team based in London. What You’ll Do Own and manage the full lifecycle of both ML models and core infrastructure - from development and deployment to monitoring and continuous improvement. Build and maintain robust CI/CD pipelines for both software … ML workflows. Ensure reliability, scalability, observability, and security of production systems and ML infrastructure. Automate deployment, orchestration, and environment management using modern DevOps tooling. Collaborate closely with software engineers, data scientists, and product teams to bring ML-powered features to production. Proactively detect, troubleshoot, and resolve infrastructure and model performance ...

complete the application to adjustments@depop.com. Role Depop is looking for a Staff Machine Learning Scientist to join our new Core ML team in the UK. You will work alongside a multi-functional team of Product Managers, ML Engineers, and fellow ML Scientists, helping build and maintain foundational … evolve them as shared systems Partner closely with senior stakeholders across the business to define problems, and lead the design of general-purpose, scalable ML solutions that power features like content understanding, moderation, and personalisation Lead the end-to-end lifecycle of large-scale experiments, from hypothesis generation through evaluation ...

help create digital agents that can understand customer needs, access relevant knowledge, and successfully complete complex tasks. You will work closely with AI/ML engineers, software engineers, product managers, and other data scientists to take ideas from experimentation through production. You will have significant ownership of data science solutions … evaluation. Partner with data and engineering teams to build and maintain reliable pipelines for model training, evaluation, and production use. Contribute to scalable ML/AI pipelines that support experimentation, deployment, monitoring, and continuous improvement. Ensure solutions are reproducible, maintainable, and designed to operate effectively at production scale. Collaboration Partner ...

learning platforms such as AWS, Azure, GCP, and Databricks, as well as the broader ecosystem used to build and deploy AI and ML products Deep expertise in artificial intelligence, with a track record of implementing advanced AI solutions to drive strategic transformation and operational efficiency. Strong experience using … Master's or Ph.D. in a related discipline is preferred, but not required Responsibilities Lead the design, development, and delivery of innovative AI, ML, and GenAI solutions that create meaningful value for clients and advance product capabilities across the Corporate and Governments business. Lead the end-to-end design, development ...

learning platforms such as AWS, Azure, GCP, and Databricks, as well as the broader ecosystem used to build and deploy AI and ML products Deep expertise in artificial intelligence, with a track record of implementing advanced AI solutions to drive strategic transformation and operational efficiency. Strong experience using … Master's or Ph.D. in a related discipline is preferred, but not required Responsibilities Lead the design, development, and delivery of innovative AI, ML, and GenAI solutions that create meaningful value for clients and advance product capabilities across the Corporate and Governments business. Lead the end-to-end design, development ...

applying AI technologies to real-world business challenges. Requirements Key Responsibilities Design, develop, and maintain high-performance Java-based applications Integrate AI/ML models into production-grade backend systems Build RESTful APIs and microservices using modern Java frameworks Collaborate with data scientists to deploy and scale machine learning … deploy AI-powered services Contribute to architecture decisions and technical roadmaps Design, develop, and maintain high-performance Java-based applications Integrate AI/ML models into production-grade backend systems Build RESTful APIs and microservices using modern Java frameworks Collaborate with data scientists to deploy and scale machine learning ...

consideration and company funding. Your main responsibilities will be to Have an in-depth knowledge of the management, methods for development, methods for deployment, ML-Operations and procurement of AI solutions in multiple projects and/or solution elements, and specifically: Understanding and Management of Generative AI and associated technologies … that corporate AI capability is advanced. Support workshops, discovery activities and requirements gathering. Be adept with both Predictive Analytics environments as well as ML Classifiers. Develop solutions for, and in deploying on, public and private cloud technologies, particularly Azure or AWS. Manipulate, process, and extract value from large, disconnected datasets ...

build production-ready AI features that empower business users to leverage the power of GenAI within their planning workflows, requiring both deep ML knowledge and strong software engineering skills. Your Impact Lead the architecture, design, and deployment of scalable Generative AI and Machine learning systems into production environments. … production environments Implement monitoring, logging, and observability for GenAI systems to track usage, errors, and model behaviour Collaborate with data scientists to productionise ML models and forecasting algorithms Your Skills Extensive hands‐on professional experience in the field of Artificial Intelligence, Machine Learning, or related engineering domains. ...

ReqID: FEQ427R340 Location: London Skills: Data Science, Machine Learning, AI, LLM, GenAI Mission As a Senior Specialist Solutions Architect (ML & AI), you will serve as the trusted technical ML and AI expert for Databricks customers and the Field Engineering organization. You will partner with Solution Architects to guide … enterprise and strategic customers in architecting production-grade ML and AI applications on the Databricks Data Intelligence Platform. You will also continue to sharpen your technical expertise in cutting-edge areas like GenAI, ML, MLOps, and LLMOps, while mentoring colleagues and establishing yourself as an AI thought leader. Impact ...

Role AI Evangelist (Senior Technology Architect) Technology, Location & Compensation AI/ML/Gen AI, Data Science, Poly Cloud – Azure, AWS, GCP London, UK Competitive (including bonus) Job Summary We seek a highly skilled senior architect/consultant to lead the Generative AI Technologies team. The candidate must possess deep … accuracy, cost and latency. Understanding of AI governance, security, privacy, bias/fairness and emerging regulations. Machine Learning Mastery – profound understanding of ML principles, algorithms, frameworks, and training pipelines. Technical Proficiency – programming in Python, TensorFlow, PyTorch or similar; modern LLM/agent frameworks; cloud AI platforms (Amazon Bedrock ...

solutions. Typical engagements include: Engineering large-scale data ingestion and processing pipelines Designing data lakes and distributed data platforms Enabling analytics and AI/ML workloads Supporting intelligence data exploitation workflows Integrating multiple classified data sources across secure environments Job Responsibilities Design, build and maintain secure, scalable data platforms capable … Ensure data quality, reliability and performance through monitoring, validation and operational support mechanisms. Collaborate closely with data scientists to enable analytics and AI/ML workloads, including feature pipelines and data preparation processes. Optimise data storage and processing architectures to support high‐performance analytical environments. Contribute to DevSecOps and cloud ...

solutions. Typical engagements include: Engineering large-scale data ingestion and processing pipelines Designing data lakes and distributed data platforms Enabling analytics and AI/ML workloads Supporting intelligence data exploitation workflows Integrating multiple classified data sources across secure environments Job Responsibilities Design, build and maintain secure, scalable data platforms capable … Ensure data quality, reliability and performance through monitoring, validation and operational support mechanisms. Collaborate closely with data scientists to enable analytics and AI/ML workloads, including feature pipelines and data preparation processes. Optimise data storage and processing architectures to support high-performance analytical environments. Contribute to DevSecOps and cloud ...

broad spectrum of reliability problems where data-driven approaches can be applied, combining subject matter expertise with statistical, predictive, and generative AI/ML methods to improve reliability in ways that truly matter to Google's users and customers. In this role, you will design statistical and machine learning … rebuild them. We keep our networks up and running, ensuring our users have the best and fastest experience possible. Responsibilities Design and build statistical, machine learning, and AI tools, alongside investigative data pipelines, for integration into existing or new reliability infrastructure. Apply data science to improve Google Cloud ...

Contribute to the full model lifecycle , from initial discovery and feature engineering through to production, experimentation, and continuous monitoring. Design and refine real-time ML systems that reduce false positives and ensure a smooth, secure experience for legitimate customers. Foster a responsive feedback loop , adapting models as patterns evolve … ensure our defences remain robust and effective. Help shape the technical direction of fraud prevention ML at GoCardless, exploring new approaches as we grow globally. Support the team’s growth through technical mentorship, knowledge sharing, and a commitment to high-quality code. What excites you Solving complex, dynamic problems: Developing ...

with the communities in which we work and live. It is personal to all of us. Julie Sweet, Accenture CEO Key responsibilities Deploy machine learning models to production and implement measures to monitor their performance Implement ETL pipelines and orchestrate data flows using batch and streaming technologies based … Infrastructure as Code tools (e.g. Terraform or CloudFormation) Strong understanding of data modelling and system architecture Demonstrable experience on at least one AI/ML project Knowledge of common machine learning frameworks and models A good understanding of approaches to monitoring ML models in production Experience leading ...

that power business insights, critical business capabilities, and AI-enabled decision‐making. You will work across data engineering, analytics enablement, visualization, and AI/ML engineering, contributing to reliable data pipelines, governed datasets, orchestration frameworks, and data products that enable self‐service analytics and intelligent automation across the enterprise. … reusable, and performant data products SQL, Data Modelling & Analytics Enablement Create well-modelled, trusted datasets that support reporting, visualization, advanced analytics, and AI/ML use cases Enable self‐service data access and governed consumption by building clear data contracts, documentation, and quality controls Contribute to integrated data foundations that ...

designing highly available Hybrid and Multi-Cloud architectures (Azure & AWS).* AI & Machine Learning Exposure: Experience designing architectures that support AI/ML workloads, including integrating Large Language Models (LLMs), predictive analytics, and vector search into enterprise applications.* Enterprise Governance & Security: Deep understanding of security architecture, secure SDLC … technology landscape, notably encompassing:Compute & Services: Java, .NET, Python, Cloud-native microservicesData & Analytics: Databricks, Microsoft Fabric, AWS Glue, Athena, Event Streaming (e.g., Kafka)AI & ML: Azure OpenAI, LLM Integration patterns, Vector DatabasesIntegration & Storage: Azure Data Factory (ADF), SQL Server, Enterprise relational platformsInfrastructure: Azure, AWS, and Hybrid Cloud networksCandidates ...

this programme, direct hands‐on depth across the AI engineering stack is essential: Strong general‐purpose programming (most commonly Python) applied to AI/ML systems Semantic search, vector/embedding infrastructure, and RAG pipeline construction LLM orchestration and agentic frameworks (e.g. LangChain/LlamaIndex‐style tooling, multi‐agent patterns … versioning, deployment, monitoring, and rollback for AI services in production Cloud‐native engineering across major providers (AWS, Azure, or GCP), including their AI/ML tooling Containerisation and infrastructure‐as‐code for repeatable, auditable deployments Secure‐by‐design engineering appropriate to sensitive public‐sector data AWS/Azure/ ...

managing direct reports, providing regular guidance and performance feedback Ability to create delivery plans with estimated timelines for personal and team workloads Experience supporting ML model deployment and DevOps collaboration Desirable: Degree in STEM, Data, AI, or Programming-related field Awareness of data security best practices Experience with designing data … architecture Experience with scaling infrastructure and code, (e.g. Kubernetes) Exposure to Ansible and Terraform Understanding of ML algorithms and deployment This is not an exhaustive list, and we are keen to hear from you even if you might not have experience in all the above. The most important skill ...