601 to 625 of 2,058 Machine Learning Jobs in the UK excluding London

preferable, whether thats Wealth Management, Banking, Insurance or another regulated financial organisation. Where does AI fit? You dont need to be an AI or Machine Learning Engineer. The client is looking for evidence that youve started exploring how AI can improve the way you engineer perhaps using Copilot ...

/CD, Application Resiliency, and Security Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.) In-depth knowledge of the financial services industry and their IT systems Demonstrated experience designing and scaling agentic AI-enabled development patterns ...

Microsoft Azure SQL Server, MySQL or PostgreSQL Node.js or Python AWS Docker/containerisation Automated testing and CI/CD Data analytics or machine learning Internet of Things (IoT) technologies and applications You don't need experience across the entire technology stack. A strong front-end developer with ...

agile methodologies -CI/CD, Application Resiliency, Security, and capacity planning Demonstrated expertise in a technical discipline (e.g., cloud architecture, artificial intelligence/machine learning, mobile, distributed systems, security, DevOps/platform engineering) In-depth knowledge of financial services industry and their IT systems, regulatory constraints, and operational ...

APIs that connect data services to frontend applications Work with large-scale rail inspection datasets including ultrasonic, electromagnetic, and operational data Implement and deploy machine learning models and statistical analyses in production environments Architect and manage AWS cloud infrastructure for data workloads (S3, Lambda, Glue, Athena, SageMaker, Step ...

Proven data engineering experience, with the ability to design, implement and maintain robust data pipelines. Hands-on experience working with AI, Generative AI or machine learning solutions in a practical, production-oriented context. Practical prompt engineering experience, including designing, testing and optimising prompts for large language models. experience ...

passion for working across teams. Preferred SkillsPrior experience in a people management or tech lead role within a data engineering or analytics teamFamiliarity with machine learning workflows, data observability, and streaming architecturesExperience working in a product-driven, customer-focused organizationUnderstanding of data privacy, security, and compliance frameworksABOUT FANDUELFanDuel ...

reuse. Help reduce one‐off security consultations by embedding approved security decisions into tooling, templates, and standard delivery workflows. Requirements Essential - Experience in machine learning engineering. Strong experience in cloud security engineering, application security, security architecture, DevSecOps, or security automation. Hands‐on experience with at least one major ...

business insights as well as crafting data pipelines, implementing data models, and optimizing data processes for improved data accuracy and accessibility, including applying machine learning and AI‐based techniques. Since 1935, Morgan Stanley is known as a global leader in financial services, always evolving and innovating to better ...

building a governed, interoperable data estate that enables self‐service for our business teams and provides the trusted foundation for advanced analytics, machine learning and AI to accelerate change across our industry. The Senior Data Reporting Analyst owns the provision of trusted, accurate and timely reporting, partnering directly ...

projects while ensuring consistency with overall strategy, commitments, and goals. You will gain fantastic experience working in the cloud with data analytics, AI and Machine Learning. The successful candidate will have 10 plus years of working with data projects, including leading teams and presenting business outcomes to key stakeholders. ...

resiliency, and security Overall knowledge of the Software Development Life Cycle Curiosity and foundational understanding of Generative AI, large language models, and AI/ML solutions Hands‐on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, testing, troubleshooting, or documentation) with demonstrated ...

timely, structured manner to technical and non-technical stakeholders. Stay current — Continuously evaluate and adopt emerging languages, frameworks, cloud services, and AI/ML tooling relevant to the product. Required Qualifications 5+ years of professional software engineering building and shipping complex, production-grade applications — not solely scripting, prototyping, or research.Strong ...

qualifications, capabilities, and skills: Good understanding of operating systems such as Windows, Linux (Redhat/Ubuntu) Good understanding of LLM and other AI/ML frameworks which can be used in AIOPS J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world ...

timely, structured manner to technical and non-technical stakeholders. Stay current — Continuously evaluate and adopt emerging languages, frameworks, cloud services, and AI/ML tooling relevant to the product. Required Qualifications 5+ years of professional software engineering building and shipping complex, production-grade applications — not solely scripting, prototyping, or research. ...

Expertise in Python and/or PySpark Knowledge of software application development and technical processes, with depth in disciplines such as cloud, AI/ML, or data engineering Experience in large-scale data processing, microservices, API design, Kafka, Redis, MemCached, observability tools (Dynatrace, Splunk, Grafana), and orchestration frameworks (Airflow, Temporal ...

qualifications, capabilities, and skills: Good understanding of operating systems such as Windows, Linux (Redhat/Ubuntu) Good understanding of LLM and other AI/ML frameworks which can be used in AIOPS ABOUT US J.P. Morgan is a global leader in financial services, providing strategic advice and products ...

Expertise in Python and/or PySpark Knowledge of software application development and technical processes, with depth in disciplines such as cloud, AI/ML, or data engineering Experience in large-scale data processing, microservices, API design, Kafka, Redis, MemCached, observability tools (Dynatrace, Splunk, Grafana), and orchestration frameworks (Airflow, Temporal ...

Support the identification and shaping of future AI opportunities once the first use cases have demonstrated value. Desirable skills: Azure AI Foundry and Azure Machine Learning. MLOps practices and tools such as MLflow. Containerisation and orchestration using Docker and Kubernetes. Experience developing copilots, AI agents or multi-step ...

fantastic team of technology experts. You will be responsible for designing, developing, and maintaining data pipelines and systems that enable data analysis and machine learning. You will also collaborate with data scientists, analysts, and other stakeholders to ensure data quality and reliability. Requirements Key Responsibilities: Develop Data Engineering solutions ...

with Microsoft Azure or other cloud platforms (AWS, GCP). Experience with graph databases and graph‐based data modelling. Experience contributing to AI/ML-enabled tools in a scientific or data-driven environment. Experience mentoring others or acting as a technical lead or point of reference. Experience with C# ...

Tech Lead level, with the ability to be both highly technical and an effective people manager Hands-on experience building AI/ML applications (RAG, agent frameworks, MCPs, skills, harnesses) and taking them to production or in platforming (LLM or MCP gateway, agentic runtime, auth, data retrieval, eval tooling) Experience ...

privacy‐tooling roadmap (e.g., Purview/BigID/Collibra/OneTrust) and integration with data platforms, establish controls for AI/ML across the model lifecycle aligned to Model Risk Management, track regulatory/market trends, and translate them into actionable roadmaps with clear OKRs/KRIs and senior‐level ...

handling, access control, and GDPR basics Nice to Have: RAG architecture, hybrid retrieval strategies, or prompt engineering experience Nice to Have: MLOps or ML pipeline experience Nice to Have: Domain knowledge in compliance, tax technology, or e-invoicing Due to client contractual obligations, the successful candidate will be asked ...

About the job Help prove the ML software stack that future AI systems will depend on. the company is expanding the software systems behind AI compute at datacenter scale. This role focuses on validating a complex machine learning stack before it reaches customers and hardware.You will build … raise reliability, performance and maintainability across frameworks, simulators, emulators and future hardware. You will shape test architecture across large codebases, CI pipelines and representative ML workloads. You will use strong software engineering judgement to turn complex technical goals into scalable validation systems. This is a role for someone who enjoys ...