751 to 775 of 3,268 Machine Learning Jobs in the UK

container orchestration. Experience mentoring other engineers and leading by example. Strong understanding of software architecture principles and system design. Familiarity with integrating AI/ML APIs or frameworks (e.g., TensorFlow, PyTorch) is a plus. Excellent communication skills and a collaborative approach to problem solving. The Mindset We Value: Relentless Innovation ...

large enterprise cloud platforms for hundreds or thousands of users. Experience designing or maintaining distributed systems, secure networks, or infrastructure supporting autonomy, AI/ML, or big data workloads. Demonstrated ability to work across technical disciplines, influence without authority, and operate in ambiguous and fast‐paced environments. Experience working with ...

expertise in system design, application development, testing, and operational stability Advanced proficiency in one or more programming languages and technical disciplines (cloud, AI, ML, etc.) Ability to tackle design and functionality challenges independently Demonstrated experience with enterprise-authorized AI-assisted software development tools Strong understanding of responsible AI use, including ...

Celery/SQS). Strong Python skills. Familiarity with the Datadog/Grafana observability stack. A background in offensive security, CTFs, or AI/ML infrastructure. What We Offer Competitive Salary + Significant Equity: We want you to have true ownership in the success of the company. Founding Impact ...

approach to solving customer problems. Strong capability in at least one or two of the following areas: Data Engineering, Data Warehousing, AI/ML, GenAI, AI Agents, or application development, with interest in expanding into adjacent areas over time. Exposure to domains such as CDP/Martech, customer data architectures ...

technical engine of our Innovation team, working directly with highly regulated clients to help them transform their operations using advanced AI/ML technologies. You will be an embedded builder who bridges the gap between frontier AI products and production‐grade reality within customers. Unlike traditional advisory roles, you will ...

include: Prior experience and knowledge of Barclays or and/or Banking domain knowledge will be preferred. Skills of any programming languages (like ML, AI/GenAI, Shell, Java, Python, Json or any other) will be preferred. You may be assessed on the key critical skills relevant for success inrole ...

environments with diverse stakeholders Knowledge of DevOps, CI/CD, and continuous improvement practices Demonstrated success in innovation and emerging technologies, including AI/ML Proven ability to build and lead high‐performing teams Leadership & Personal Attributes Inspiring leader with strong stakeholder management and communication skills Commercially aware, strategic ...

least 3 years in a technical lead role delivering enterprise-grade process automation. AI Implementation Track Record: Proven experience utilising existing AI/ML technologies to transform business processes and mitigate LLM-specific risks (e.g., prompt injection and data leakage). Leadership Interfacing: Demonstrated experience engaging with Senior Leadership ...

technical engine of our Innovation team, working directly with highly regulated clients to help them transform their operations using advanced AI/ML technologies. You will be an embedded builder who bridges the gap between frontier AI products and production‐grade reality within customers. Unlike traditional advisory roles, you will ...

risk, or electronic market making models. Database interfacing, data management and (pre-)processing (kdb, q, SQL). Experience of working with tensorflow and other ML packages. ABOUT US J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world's most prominent corporations, governments ...

data and AI programmes end to end • Experience leading multi‐disciplinary delivery teams across several workstreams • Experience in environments spanning data platforms, AI/ML deployment, integration, and analytics || | • Strong stakeholder engagement and executive communication skills. • Ability to navigate ambiguity, drive clarity, and make informed decisions quickly. • High emotional intelligence ...

cloud environments (AWS, Azure, or GCP). Broad experience (in two or more) and understanding across the fields of data engineering, data warehousing, AI, ML, governance, transactional systems, app development, and streaming. Undergraduate degree (or higher) in a technical field such as Computer Science, Applied Mathematics, Engineering or similar. ...

technical scopes, then collaborate closely with engineering leads to design the right solutions. Champion our core user personas (Data Engineers, DevOps, Enterprise Developers, ML Engineers) and prioritize solving their biggest pain points, from clunky integrations to slow deployment cycles. Run a consistent pipeline of user interviews with technical stakeholders ...

clustering, NLP) Model lifecycle management (training, validation, monitoring) Translating legal and business problems into analytical use cases Understanding limitations and risks of statistical and ML models Large Language Models (LLMs) and GenAI patterns RAG architectures, agentic workflows and orchestration AI service integration via APIs and model abstraction layers Runtime guardrails ...

stable production‐grade operational stage, enabling operations with robust quality control as well as continuous evolution, calibration and consolidation. Phase 3 will ensure the ML model of the Earth system piloted in phase 2 is transitioned towards a production‐ready status. For more about DestinE, see https://destine.ecmwf.int ...

finance source systems (ERP, EPM, sub‐ledgers, and consolidation tools) into governed, analytics‐ready models. Design the finance data foundations for applied AI/ML: governed retrieval sources for RAG, feature stores, and the architecture that keeps AI systems fed with trustworthy, reconciled finance data. Set patterns for secure, compliant ...

internal engineers on modern AI development workflows and best practices. Qualifications What We’re Looking For 8 - 12+ years of experience across AI/ML engineering, applied research, or AI product development. Demonstrated experience building and shipping enterprise-grade AI products. Deep familiarity with modern AI stacks (LLMs, RAG systems ...

Posted on 26/11/2025 We provide end-to-end IT solutions and services including Applications services, Data & Analytics services, AI/ML Technologies and Professional services in the UK and EU market. Job Description Role Summary We are seeking an experienced Test Manager with strong General Insurance ...

Software Engineering team at CoMind spans the full stack of a regulated medical device company from embedded and real-time systems through application software, ML inference, GUI, DevOps, and test engineering. It is a team that builds across every layer, working to medical device software standards and shipping software that ...

across the organisation, mentoring and uplifting QA capability globally. Key Skills and Competencies Strong understanding of the testing and quality challenges of non-deterministic, ML/LLM-based, and agentic systems, including evaluation, guardrails, and the regression of model-driven behaviour. Proven experience defining and implementing QA strategy ...

feedback, reviews) to discover patterns that shaped product decisions. Experience working closely with Product and Engineering teams. Hands‐on experience working with AI/ML-driven products (LLMs, ranking, generation, recommendations). You have worked on these systems, not just alongside them. Skillset Strong applied modelling skills: regression, classification, clustering ...

concrete, platform-wide technical roadmap Nice to Have Experience with event technology, SaaS platforms, or B2B applications Experience building data infrastructure that directly feeds ML models or AI agent systems Familiarity with prompt engineering, fine-tuning, or AI model optimisation Real-time systems, WebSockets, or live data pipelines Experience with ...

executive audiences Collaborate across globally distributed teams with awareness of time zone considerations and asynchronous work patterns Guide teams in embedding AI/ML features—prompt engineering, model inference, feature pipelines—into platform services Contribute to technical planning, architecture decisions, and incident retrospectives Platform & Product Mindset Apply product thinking ...

track time and bill for hours worked on customer projects. Assist sales and sales engineering on technical prospect calls when required. Leverage AI/ML capabilities to enhance integration frameworks, solution design, system automation, and operational efficiency. Support the responsible use of AI-driven approaches in cloud-based solutions, DevOps ...