76 to 100 of 3,210 Machine Learning Jobs in London

continue to break records across countries, channels and categories, we’re looking for extraordinary talent to join us. 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. … solve problems using existing AI tools where possible and build custom solutions when needed. Our 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 ...

Labs (SAIL) practice is looking for an experienced Senior Manager to lead consultancy engagements and grow our AI & Solutions Engineering capability.The AI/ML Senior Manager role will lead the delivery of AI-enabled solutions embedded in our clients' teams, combining deep technicalspecialism with the commercial and leadership skills … Learning solutions directly embedded into business processes. We support clients across a number of industries and offer deep expertise in AI/ML, Cloud, Platform Engineering, and Managed Solutions. What you will be doing As a Senior Manager in SAIL, you will own and lead consultancy engagements ...

Director of AI/ML within the Commercial and Investment Bank, you will set the vision and lead the enterprise portfolio for agentic AI that automates and optimizes complex business workflows at scale. You will guide cross-functional teams and strategic partners to define reference architectures and delivery roadmaps … field.Significant proven experience building and deploying AI applications in large scale production environments.Experience managing data science teams and couching team membersProficiency in Python and ML frameworks (PyTorch, TensorFlow, scikit-learn).Hands-on experience with agentic frameworks (LangChain, CrewAI, AutoGen, LangGraph, ADK).Experience with generative models (transformers, GANs/VAEs; diffusion ...

seeking an experienced, technical, and hands-on Autonomy Data Manager to grow and lead a talented team composed of Data Scientists, Data Engineers and ML Ops Engineers, working in the Autonomy team to deliver data driven Planning and Perception solutions. You will lead the team to drive the creation … provide technical guidance in the design, development, deployment, optimization, and evaluation of state‐of‐the‐art data algorithms, data efficiency and pipelines to enable ML model performance with a focus on iteration speed, scalability and overall cost efficiency.Drive a culture of rigorous statistical evaluation to measure, validate and implement evaluation ...

cost-effective AI solutions.This is a hands-on technical leadership role, ideal for someone currently operating as a Lead AI Architect, Principal AI/ML Engineer, AI Engineering Lead, Principal Architect, AI Practice Lead or similar, and looking to take the next step into an Associate Director-level position.The RoleAs … enterprise and public sector environments.Lead the development and deployment of production-grade Generative AI and Machine Learning solutions.Architect systems integrating LLMs and ML models into wider enterprise applications and workflows.Oversee the full technical lifecycle, from solution design and model selection through to deployment, monitoring and continuous improvement.Design ...

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 ...

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 Platform reliability in partnership with the Platform Reliability Engineering (PRE) organization, focusing on change supervision and rollouts.Collaborate closely with engineering … 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 ...

clients, understanding their needs, and translating them into effective outcomes. 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 … 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 ...

Vacancy detailSenior AI/ML Engineer90,000 - 110,000 GBPNo Hybrid WORKINGLocation: UK wide , Central London, Greater London – United Kingdom Type: PermanentSenior AI Engineer – London (Remote)We're looking for an experienced AI Engineers to lead the next generation of AI-powered learning experiences. You'll play a pivotal … defining our AI 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 RoleAs an AI Engineer ...

lessons learned fast. Be the kind of leader who creates that energy and channels it into things that last. Push the frontier of AI, ML, and intelligent systems Go beyond adopting AI tools — define how intelligent systems become structural, load-bearing parts of the platforms your teams own. Whether that … powered workflows, ML models embedded in analytical processes, agentic automation, or AI-augmented developer tooling, bring the depth to evaluate, architect, and champion these capabilities with real technical conviction. If you've built ML systems from the ground up, that experience will resonate deeply here — and you'll have ...

system architecture.Experience pair programming collaboratively with other developersExposure to or interest in working with modern AI systems (LLMs, agent frameworks, cloud deployment). ML experience is a plus but not required.Nice to have: Experience with cloud deployment (Azure/AWS/GCP), containerization (Docker), frontend frameworks (React), CI/… large-scale, complex projects—including open-sourcing some of these frameworks, such as Kedro and ARK—and developing innovative, industry-specific AI/ML solutions that embed our distinctive technical approach and business knowledge for enterprise clients.As a Software Engineer II, you will collaborate with interdisciplinary teams to design ...

best practices to enhance team efficiency and delivery excellence.Connect to your skills and professional experienceTechnical Proficiency:Proven experience with Python and popular AI/ML libraries such as TensorFlow, PyTorch, scikit-learn.Strong understanding of machine learning algorithms, deep learning architectures, and statistical modelling techniques.Experience with cloud computing … platforms (e.g., AWS, Azure, GCP or equivalent) and their AI/ML services.Proficiency in data manipulation and analysis using SQL and big data technologies (e.g., Spark, Hadoop) is a plus.Experience with MLOps tools and best practices for model deployment, monitoring, and governance.Education and Experience:Bachelor's or Master ...

Enterprise Architect — Artificial Intelligence AI/ML Infrastructure, Platform & Governance Role Summary World Wide Technology is looking for a deeply technical Enterprise Architect who will own the delivery of AI projects end to end from the silicon and data center design that underpins AI workloads, through the software and MLOps … while mentoring delivery teams and shaping WWT's broader AI point of view. Key Responsibilities Own end-to-end technical delivery of AI/ML engagements: architecture definition, design authority, build oversight, and go-live validation. Host and chair Architecture Review Board (ARB) and Technical Design Authority (TDA) sessions ...

others to deliver advanced AI and data solutions at citizen scale. Our 150-strong AI and Data Practice brings together deep expertise in machine learning, generative AI, agentic AI and data. We are pioneers in responsible AI, having authored the UK government’s AI Cyber Security Code … 2.1 degree in Computer Science, AI, Data Science, Statistics or in a similar quantitative field. Demonstrable experience of deploying modern AI/ML solutions into production, including prompt engineering, retrieval-augmented generation (RAG), model evaluation, and monitoring using metrics (e.g. precision, recall, NDCG and drift detection). Strong Python skills ...

others to deliver advanced AI and data solutions at citizen scale. Our 150-strong AI and Data Practice brings together deep expertise in machine learning, generative AI, agentic AI and data. We are pioneers in responsible AI, having authored the UK government's AI Cyber Security Code … 2.1 degree in Computer Science, AI, Data Science, Statistics or in a similar quantitative field. Demonstrable experience of deploying modern AI/ML solutions into production, including prompt engineering, retrieval-augmented generation (RAG), model evaluation, and monitoring using metrics (e.g. precision, recall, NDCG and drift detection). Strong Python skills ...

DescriptionCertificationsNVIDIA certifications (NCP-AI Infrastructure, or NVIDIA Deep Learning Institute credentials) — strongly preferred.Cloud AI/ML certification: AWS Certified Machine Learning – Specialty, Microsoft Certified: Azure AI Engineer Associate, or Google Professional Machine Learning Engineer — at least one preferred.Kubernetes: CKA or CKAD — preferred.TOGAF 9/… ExperienceBachelor's degree in Computer Science, Computer Engineering, or a related technical field, or equivalent demonstrable experience.Advanced degree (MS in CS/AI/ML or related) beneficial but not required given sufficient hands-on depth.Continuous, demonstrable learning in AI — publications, open-source contributions, conference speaking, or lab-based ...

clean, efficient, and scalable code that adheres to software engineering principles, MLOps practices, and cloud-native development. AI Solution Delivery: Own the implementation of ML pipelines, APIs, and data integration workflows. Operational Excellence: Contribute to defining reusable development patterns, enforcing coding standards, and implementing MLOps best practices that support version … processing or other relevant AI fields. Proven track record of designing, developing, and deploying AI systems in production environments. Proficient in Python and key ML libraries (e.g. PyTorch, PySpark, scikit-learn, Hugging Face Transformers). Hands-on experience with modern data platforms and AI tooling such as Azure ML, Databricks ...

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 ...

capabilities or “engines” that integrate directly into Anaplan Applications to solve complex enterprise business problems. In this role, you will develop best-in-class ML models and pipelines to drive automated, actionable insights at scale. Beyond core development, you will act as a key technical partner for our customers. … will play a highly visible role in driving customer onboardings, getting hands-on with client data to customize and fine-tune our ML engines so they seamlessly adapt to complex business realities and specific customer needs. Your Impact Customer Onboarding & Engine Customization: Lead the technical deployment of our engines ...

approaches for extracting insights from structured and unstructured data for our core customer base – Corporates, Banks, Professional Services, and Asset ManagersDevelop and maintain robust ML and data pipelines for experimentation and deployment.Design, build, and optimize risk models for analytics and generative AI applications using our proprietary NLP data generation process.Collaborate … cross functionally with Economists, Industry Analysts, Political Scientists, and Developers.Explain ML/NLP model outputs and methodologies to non-technical stakeholders.You May be a Good Fit if:Substantial experience querying, cleaning, compiling, and analyzing big data.Familiarity applying various computational social science methods including data mining, data visualization, natural language processing ...

clients and with the communities in which we work and live. It is personal to all of us.” – Julie Sweet, Accenture CEOKey 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 … 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 ...

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 ...

DescriptionRole – AI Evangelist (Senior Technology Architect) Technology – AI/ML/Gen AI, Data Science, Poly Cloud – Azure, AWS, GCP Location – London – UKBusiness Unit – TOPAZDLVRYCompensation – Competitive (including bonus)Job Summary: We are seeking a highly skilled and experienced Senior Architect/Consultants to lead our Generative AI Technologies team. … ideal candidate will have a deep understanding of Generative and Agentic AI, LLMs, retrieval-augmented generation (RAG), machine learning, and modern interoperability standards such as the Model Context Protocol (MCP), along with a proven track record of architecting and implementing innovative, enterprise-scale solutions. As a Senior Architect ...

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 ...

Foundational Research is the dedicated core Machine Learning research division of Thomson Reuters. We focus on advanced algorithms and training techniques for Large Language Models (LLMs) and Data-Centric Machine Learning.While our Research Scientists push the boundaries of what models can do, the Research Engineering team defines … Experience working in a Research Lab or "0-to-1" innovation environment.Experience owning the end-to-end lifecycle of an internal developer platform or ML tooling product, including defining adoption metrics and iterating based on user research.Background in Platform Engineering.Experience contributing to open-source LLM or NLP libraries.As part ...