126 to 150 of 6,121 Machine Learning Jobs in the UK

will own the data and model layers of our client projects: designing and building the pipelines that feed AI systems, developing and deploying ML and LLM‐powered solutions, and standing up the RAG pipelines and agentic AI systems. Your role will include planning, tool use, and human‐in‐the‐loop … proof‐of‐concept builds for new client engagements, including AI readiness and data assessments Experience 3‐5 years of professional experience across AI/ML engineering and/or data engineering in a commercial or consultancy setting Strong, demonstrable proficiency in Python for data and ML work Advanced ...

reliability practices (SLOs, error budgets, runbooks) and leads production incident response and post-incident reviewBuilds and operates observability across the team's AI/ML services (metrics, logging, tracing, alerting)Automates infrastructure provisioning and configuration through infrastructure-as-codeImplements operational security, secrets management, and access controls to firm-wide standardsPartners … high-availability environmentMaster's degree in Computer Science, Engineering, or a related technical field (or equivalent applied experience)Preferred qualifications, capabilities, and skillsExperience operating ML/LLM workloads in production (MLOps, inference reliability, cost/performance management)Experience within financial services technologyFamiliarity with JPM-internal platform, cloud, and observability tooling ...

organization. We partner with teams across the firm to solve some of the most complex and consequential challenges in financial services, applying generative AI, machine learning, optimization, and statistics to deliver measurable business impact. Our mission is simple but ambitious: combine human and machine intelligence to revolutionize … including supporting their career growth and development. Strong familiarity with Python programming, and hands-on experience guiding solutions architecture for production-grade AI/ML systems. Strong theoretical background in and practical experience using AI, machine learning, optimization, or statistical techniques. Experience assessing performance of machine learning ...

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 ...

production standard, with object oriented design, testing and code review as standard practice Models you've personally taken into production and supported in life Machine learning across the usual toolkit: scikit … learn, pandas, NumPy, statsmodels or similar MLOps and CI/CD in practice. Pipeline orchestration, model versioning, automated deployment, monitoring and retraining Cloud based ML delivery, ideally Azure (Azure ML, Azure DevOps). Strong AWS or GCP considered SQL and relational data modelling against large datasets Version control, branching strategy ...

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 ...

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 ...

career adventure where your ideas matter and your skills drive change. As a Senior Lead Software Engineer, Cloud Platform in the Corporate AI and Machine Learning Data Platforms team, you will design and deliver secure, high-quality technology solutions that support our data and analytics strategy. You will … infrastructure-as-code technologies. Experience implementing multi-cloud architectures and leading end-to-end platform development. Background in designing and developing scalable AI/ML or Data platforms. Experience with automation and workflow orchestration for operational efficiency. Published contributions to open-source or industry-recognized projects. Hands‐on experience building ...

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 ...

build effective internal and external relationships Strong influencing and negotiation skills Creative thinker with the ability to propose innovative solutions Passion for continuous learning and self‐development Leadership capability, either formally or through delivery ownership To qualify for this role, you must have: Multi-skilled experience … client offerings, and we help companies to further improve their efficiency with modern processes and technologies, such as Machine Learning (ML) and Artificial Intelligence (AI). Our consultants are at the heart of everything we do, and we have been recertified as a 2025 Great Place to Work ...

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 Security Clearance This role is subject to pre-employment screening in line with the UK Government’s Baseline Personnel Security Standard (BPSS). An additional range of Personnel Security Controls ...

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 ...

built in. Build platforms that support rapid experimentation while meeting production standards for latency, scale, monitoring, SLOs, playbooks, and operational excellence. Partner closely with ML engineers, product engineers, data scientists, and platform teams across DoorDash, Wolt, and Deliveroo to turn emerging GenAI capabilities into durable platform primitives. Shape the future … years of industry experience in software engineeringStrong backend engineering fundamentals, especially in Python and distributed systems. Experience building production services, APIs, data pipelines, or ML infrastructure at scale. Experience operating systems in production, including observability, debugging, reliability, incident response, and performance/cost optimization. Hands-on experience with LLM inference ...

Path Award-Winning Culture & Community Outreach Why Ryan? Competitive Compensation and Benefits Business Connectivity Reimbursement (Phone/Internet) Gym Membership or Equipment Reimbursement LinkedIn Learning Subscription Flexible Work Environment Tuition Reimbursement After One Year of Service Accelerated Career Path Award-Winning Culture & Community Outreach The Full Stack AI Engineer … while maintaining ownership and understanding of the code produced. Education And Experience Bachelor’s or master’s degree in Computer Science, Engineering, AI/ML, or a related technical field, or equivalent relevant experience. Suitable for recent graduates and candidates with approximately 0-3 years of professional software engineering experience. ...

clients. Join our engineering teams that build massively scalable software and systems, architect low latency infrastructure solutions, proactively guard against cyber threats, and leverage machine learning alongside financial engineering to continuously turn data into action. Create new businesses, transform finance, and explore a world of opportunity … coordinate multi-step diagnostic and remediation tasks. AIOps & Intelligent Observability: Ability to integrate traditional observability stacks (e.g., Datadog, Prometheus, OpenTelemetry) with AI/ML models to automate root-cause analysis, anomaly detection, and semantic log clustering. Self-healing Infrastructure Engineering: Experience designing closed-loop, self-healing systems that autonomously execute ...

enterprise architecture, solution architecture, technology consulting, systems integration, software engineering, data architecture, or related roles.5+ years of experience designing or delivering AI, data science, machine learning, advanced analytics, or intelligent automation solutions.2+ years of hands-on or architecture experience with GenAI, LLMs, RAG, AI agents, orchestration frameworks … equivalent work experience. Preferred Skills: Master's degree in computer science, engineering, data science, AI, or a related field. Cloud, enterprise architecture, AI/ML, cybersecurity, or data platform certifications. Experience with platforms such as Azure, AWS, GCP, OpenAI, Anthropic, Mistral, Google/Gemini, Databricks, Snowflake, Kubernetes, vector databases ...

AIML Data Platforms and Chief Data and Analytics Team , you will lead a team of 3-7 SRE engineers and scale the AI/ML Data Platform, deliver advanced technology products focused on data and analytics. You will tackle complex cloud data platform challenges, especially around Data Lake Tools. … operational excellence. Performs platform design, set-up and configuration, workspace administration, resource monitoring, providing engineering support to Data Engineering teams, Data Science/ML, and Application/Integration teams. Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions ...

expand platform usage. The Impact You Will Have Independently lead technical discovery and solution design for customer workloads spanning data engineering, analytics, GenAI and machine learning Build and deliver compelling proofs-of-concept and live demos on the the company Platform that drive technical wins Own frontline technical … leading technical customer conversations — discovery, whiteboarding, architecture reviews Familiarity with one or more: data engineering (ETL/ELT, medallion architecture, streaming), data science/ML (model training, MLOps), or SQL analytics Strong presentation and demo skills — you will build and present a live solution during the interview Bachelor ...

analytics insights for clients and McKinsey teams involved in transformation programs globally. Задачи Design, build, and optimize scalable data solutions for analytics, reporting, and machine learning Develop robust data ingestion pipelines, procure data from APIs, and integrate it into cloud-based storage layers Clean and standardize data … cloud-based data platforms for rapid business data access and emerging technology incubation Design and develop scalable, reusable data products for analytics, reporting, and machine learning pipelines Implement query tuning, indexing, partitioning, and caching strategies in platforms such as Snowflake and Databricks Collaborate with data scientists, engineers ...

Machine Learning solutions embedded directly into business processes. We support clients across a range of industries and offer deepexpertisein AI/ML, Cloud, Platform Engineering and Managed Solutions. We are looking for an experienced Senior Manager to serve as an AI Architect — someone who can design … deliveryaccountabilityand client advisory skill — someone energised by the complexity of taking AI solutions to production at scale. 7+ yearsin technology consulting,architectureor AI/ML engineering, with at least 3 years in a senior leadership or lead-architect role — including accountability for end-to-end solution design,resourcingand commercial outcomes. ...

Implement and continuously improve machine learning and AI operations frameworks Design and deliver tools, framework components and engineering practices for production-ready ML and AI systems Coach and guide a small team of MLOps Engineers, Analytics Engineers and AI Engineers Collaborate with Data Science, Pricing, Data Engineering … Software Development teams Evolve Machine Learning and AI Engineering standards and frameworks Enhance data pipelines and engineering infrastructure for scaled ML and AI solutions Support data acquisition, transformation, model discovery and development Ensure model auditability, versioning and data security Design and implement cloud AI Ops using Azure Optimise ...

Experience building or integrating AI-powered applications and services. Familiarity with Large Language Models (LLMs), Generative AI, Retrieval-Augmented Generation (RAG), AI agents, or machine learning workflows. Experience integrating AI APIs and platforms such … OpenAI, Anthropic, Azure AI, or similar technologies. Knowledge of vector databases, embeddings, prompt engineering, and AI application architecture. Experience with Python for AI/ML-related development. Exposure to MLOps practices and AI model deployment pipelines. Contributions to open-source projects or technical communities. Competitive Salary Bonus Scheme Private Healthcare ...

Time Analyst in the Data & AI Program at JPMorganChase, you will drive impact by building end-to-end data, analytics, and artificial intelligence and machine learning solutions that translate business objectives into measurable outcomes for clients and customers. Working alongside global experts in collaborative teams, you will design … career in a culture where we value your ideas and help you grow. Job Responsibilities Build intelligent systems that power real business outcomes, from machine learning models to generative artificial intelligence and agent-based solutions. Work hands-on with cutting-edge technologies to design, develop, and deploy artificial ...