351 to 375 of 1,108 Machine Learning Jobs in the UK

Programming Job Reference: BBBH 25049a Keywords: Software, Developer, Engineer, Python, OOP, Object, Oriented, Programming, TypeScript, Vue, C++, Product, Marine, Defence, Machine, Learning, ML, Mechatronics, Robotics, Computer, Vision, IoT, Sensor, System, Integration, Hybrid, Lancaster, Lancashire If you're interested in this role, click 'apply now' to forward ...

underrepresented groups, and neurodivergent candidates. We offer reasonable adjustments throughout the hiring process and are dedicated to creating a supportive, accessible environment for everyone. Machine Learning Ops Engineer Location: Ersk... ZIPC1_UKTJ Company DXC Qualifications Senior (5+ years of experience) #J-18808-Ljbffr ...

some of the UK's most important organisations, this is the role. Key Responsibilities Lead the delivery of complex, production-grade AI and ML solutions at scale across major client programmes Provide technical and thought leadership to C-level and senior stakeholders, defining architectural principles and strategic direction Drive adoption … wider AI community through thought leadership, research and industry engagement What You'll Need Essential: Proven track record delivering complex, production-grade AI and ML solutions at scale Deep expertise in advanced AI and ML models including time series, supervised and unsupervised learning, reinforcement learning, LLMs and agentic ...

participation. What You'll Bring *Degree in Engineering, Computer Science, Data Science, Electronics, or similar (Essential) *Proven experience designing, training, and deploying AI/ML models (deep learning/classical ML) on real-world problems (Essential) *Hands-on skills integrating and deploying AI solutions on edge or resource-constrained … constraints. (Essential) *Embedded system development using RTOS, with experience in debugging and troubleshooting target hardware. (Desirable) *Postgraduate qualification or formal training in AI/ML, data science, human-computer interaction or related specialism. (Desirable ...

innovation. The Chief Data and Analytics Office is responsible for building enterprise-scale, cutting-edge platforms for Data Management & Analytics and AI/ML Operations that are used firm-wide by the JPMC workforce for Artificial Intelligence (including generative AI)/Machine Learning (AI/ML) development ...

title: Senior Generative AI Architect Location: London, UK Work mode: Hybrid Skills: AI/ML architecture; AI frameworks; AI models & solutions; cloud platforms (e.g., AWS, Azure, Google Cloud) and programming languages such as Python, Java, or C++. We at Coforge are looking for Senior Generative AI Architect in London, UK. … architectures, processes, and best practices. Establish and maintain coding and architectural standards. Experience: Minimum of 7 years of experience in AI/ML architecture or a related role. Proven experience in designing and deploying generative AI models and solutions. Hands-on experience with AI frameworks and tools such as TensorFlow ...

iProov is looking for a highly capable Senior ML Infrastructure Lead to build and scale technical foundations for machine learning operations. This hybrid role involves leading the design of ML platforms and infrastructure, ensuring effective deployment and monitoring of models. The ideal candidate has extensive MLOps experience, strong ...

delivering real, production-ready outcomes. Key Responsibilities Define and implement the AI architecture strategy and roadmap Design scalable, secure, and high-performance AI/ML solutions Translate business requirements into end-to-end AI architectures Lead the design of data pipelines, model training environments, and deployment frameworks Implement best practices … technology, with a strong focus on AI, machine learning, and data architecture Proven track record of delivering enterprise-scale AI/ML solutions in complex environments Experience defining and implementing AI architecture strategies and roadmaps Strong hands-on experience building end-to-end AI systems (data pipelines, model ...

Strong understanding of external agent ecosystems and interoperability. Proven Track Record – Experience in prompt engineering, agent lifecycle management, and hands‐on prototype development. AI & ML Expertise – Experience with machine learning concepts (predictive and generative AI), plus the ability to communicate value to diverse audiences. Data Stack Knowledge – Deep … e.g., Hyperscaler SDKs to Salesforce Flows). Multimodal Pipelines – Prior exposure to conversational voice pipelines or multimodal integrations via hyperscaler services. Advanced AI/ML Frameworks – Exposure to frameworks (TensorFlow, PyTorch), MLOps practices, and cloud AI platforms like Google Vertex AI or AWS Sagemaker. Education – BS in Computer Science, Engineering ...

extracting insights from structured and unstructured data for our core customer base – Corporates, Banks, Professional Services, and Asset Managers Develop 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. Strong appreciation of software engineering fundamentals such as code quality, code ...

platform for the LGBTQ+ business community. Please do not contact the recruiter directly. Position Overview As the Technical Product Owner for the AI/ML Platform, you will own the vision, roadmap, and delivery of the core engineering and MLOps capabilities that empower our data scientists and developers. You will … crucial link between the advanced needs of our AI/ML practitioners and the platform engineering teams that build the foundational tools. This role requires a deep technical understanding of the machine learning lifecycle and the ability to translate architectural and data science requirements into a clear, actionable ...

technical audiences; influence product roadmaps, prioritization, and resourcing via data-driven analysis, scenario studies, and clear articulation of trade-offs. Lead development of ML/AI solutions end-to-end (feature engineering, model training/validation, MLOps, monitoring and drift management) with rigorous controls, documented governance, and demonstrable business value. … differentiation). Experience with market risk, time-series/stress analytics, model risk governance, and regulatory expectations for pricing/risk models. Hands-on ML/AI for quant finance (signal extraction, surrogate modeling, anomaly detection), including MLOps, drift monitoring, and explainability. Knowledge of portfolio optimization, hedging algorithms, execution analytics ...

Understanding of logging and monitoring using tools such as Cloud Logging, ELK Stack, AppDynamics, New Relic, and Splunk. Advanced Tech: Knowledge of AI and ML tools is a plus. Certifications: Google Associate Cloud Engineer or Data Engineer certification is a plus. Domain Specifics: Experience in data engineering or data science. ...

global marketing campaigns on platforms such as Google, Meta and Apple.In this role, you will:Drive product development across data, automation, and AI/ML capabilities to support marketing scalability and efficiency.Collaborate with engineering, data science, and analytics teams to deliver robust measurement and optimization tools.Translate complex technical concepts into … degree in Computer Science, Engineering, Data Science, or equivalent experience.8+ years of product management experience, ideally in marketing platforms, data products and AI/ML applications.Strong technical acumen with experience in data engineering, workflow orchestration, and machine learning operations.Excellent communication skills with the ability to influence cross-functional ...

Datadog, Soda, SSRS, etc. Cloud: Azure, AWS (S3) basic Others: REST APIs, ElasticSearch, New Relic, CI/CD, ETL, Swagger, Postman, Rancher, Data Analytics, ML Models, GitHub Copilot, Jira and Confluence. Need Hands on AI skills. Key Responsibilities Full Stack Development: Build and maintain scalable web applications using Java (Spring … Boot), Python (Fast API/Django), or Node.js for the backend. AI/ML Integration: Work closely with Data Scientists to deploy and integrate ML models (including LLMs, Predictive Models, and NLP) into production environments via RESTful APIs. Database Management: Design and optimize schemas for both SQL (Oracle, PostgreSQL ...

seeking a Head of Machine Learning & AI, based in Manchester (Hybrid). In this pivotal leadership role, you will define and oversee ML strategies that enhance customer experience across one of the UK’s top consumer platforms. Your responsibilities will include leading a team in production ML systems ...

Senior AI/ML Data Scientist - VP London | Front Office | Equities/Prime Services Currently partnering with a major global financial institution hiring a senior VP-level AI/Machine Learning Data Scientist into a highly visible front-office AI Lab environment. The team is focused on applying … advanced ML, neural networks, and predictive modelling techniques to highly complex portfolio, equities, and client behaviour problems within a large-scale Prime business generating substantial annual revenues. The environment is: highly technical delivery-focused commercially driven exceptionally fast paced Strong preference for candidates who have: built and deployed ML models ...

technical audiences; influence product roadmaps, prioritization, and resourcing via data‐driven analysis, scenario studies, and clear articulation of trade‐offs. Lead development of ML/AI solutions end‐to‐end (feature engineering, model training/validation, MLOps, monitoring and drift management) with rigorous controls, documented governance, and demonstrable business value. … differentiation). Experience with market risk, time‐series/stress analytics, model risk governance, and regulatory expectations for pricing/risk models. Hands‐on ML/AI for quant finance (signal extraction, surrogate modelling, anomaly detection), including MLOps, drift monitoring, and explainability. Knowledge of portfolio optimisation, hedging algorithms, execution analytics ...

emerging trends in LLMs, GenAI, and AI tooling Experience Required Strong commercial experience (typically 4-8+ years) in software engineering, data science, or machine learning Proven experience building and deploying LLM/Generative AI applications in production environments Hands-on experience with RAG architectures, embeddings, and vector ...

Kubernetes. Familiarity with event-driven architecture and message brokers (e.g., Kafka, RabbitMQ). Knowledge of front-end performance optimisation and accessibility standards. Exposure to machine learning pipelines or data engineering workflows. Prior experience working in startup environments or high-growth technology companies. Benefits Hybrid working as standard ...

technical leadership roles. Strong experience in Azure cloud architecture and enterprise application delivery. Experience working with Dataiku for analytics, data pipelines, or AI/ML-driven applications. Strong knowledge of .NET/ASP.NET Core architecture and enterprise integrations. Experience with financial services, treasury, derivatives, or risk management platforms. Understanding ...

teams, supporting capability growth through mentoring, coaching and creating a collaborative, high performing environment Experience Required: Strong Python and SQL experience Applied AI engineering, ML engineering or software engineering background Experience with LLMs, RAG, embeddings, prompt engineering or fine tuning Exposure to LangChain, LangGraph, Agent Development Kit or similar agent ...

teams, supporting capability growth through mentoring, coaching and creating a collaborative, high performing environment Experience Required: Strong Python and SQL experience Applied AI engineering, ML engineering or software engineering background Experience with LLMs, RAG, embeddings, prompt engineering or fine tuning Exposure to LangChain, LangGraph, Agent Development Kit or similar agent ...

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open‐source AI projects or published research in AI/ML. Extensive experience in software or systems architecture, with strong focus in AI/ML domains. Proven experience designing and deploying AI solutions using frameworks such as LangChain, RAG, and vector databases or the MCP protocol. Deep understanding of LLMs … prompt engineering, model evaluation, and fine‐tuning strategies. Strong proficiency in ML frameworks (e.g., TensorFlow, PyTorch) and cloud platforms (AWS, Azure, GCP). Experience with AI infrastructure components including model gateways, orchestration layers, and observability tools. Familiarity with AI governance, data privacy, international regulation and ethical AI frameworks. Excellent leadership ...