5 of 5 Azure Machine Learning Jobs in the City of London

Role: Azure AI DevOps Engineer Salary: £50,000 Location: London or remote Benefits: Healthcare and great holidays The Role As a Machine Learning Operations Engineer, you will be instrumental in designing, deploying, and maintaining machine learning systems that drive data-driven decision-making in the pensions and financial services … 's cloud ecosystem, you will build scalable ML workflows that support actuarial modelling, risk prediction, and client insight generation. Key Responsibilities 1. Azure-Based Machine Learning Development * Collaborate with domain experts and analysts to design and implement machine learning models that predict key outcomes such as life expectancy … investment return scenarios, and financial risks. * Deploy and manage ML solutions using Azure Machine Learning (Azure ML), covering training, testing, and deployment to production. * Select appropriate ML techniques (e.g., classification, regression, ensemble methods, survival models) to improve predictions and automate core processes. 2. MLOps & Model Lifecycle Management * Own the end More ❯

science professional looking to take the next step in your career? Campion Pickworth are working with a leading International professional services firm to recruit for Data Science and Machine Learning Assistant Manager to support the delivery of innovative analytics and machine learning solutions in a fast-paced, supportive environment. This is a … shaping our data capabilities and delivering meaningful insights that support business-critical decisions. What You’ll Do Lead the development and deployment of advanced analytics, data science, and machine learning tools and solutions. Use technologies such as Python, R, Azure, Databricks, SQL, Power BI, and Tableau to deliver actionable insights from complex data. … within cloud-based environments. Maintain high standards in code review, documentation, and delivery in a DevOps context. Apply a deep understanding of ML techniques, from supervised/unsupervised learning to generative AI and large language models. What We’re Looking For Essential Skills and Experience: Proven ability to solve complex, real-world problems through data science and analytics. More ❯

that power next-generation use cases across client intelligence, document processing, and risk management. You'll work in a greenfield environment, building compliant AI pipelines using Gemini (GCP), Azure OpenAI or Self Hosting embedding security and privacy controls from experimentation to production, in alignment with the bank's cybersecurity and regulatory standards. Accountabilities & Responsibilities Architect and implement … and compliance teams in regulated deployments Implemented or maintained controls under ISO 27001, NIST, or SOC2 frameworks Technical Skills & Technologies: Languages & Frameworks Python (FastAPI), LangChain, Google AI SDK, Azure Open AI SDK Cloud & AI Platforms GCP: Vertex AI, Gemini API, Cloud Run, GCS, IAM, Secret Manager, Audit Logs Azure: Azure ML … Azure OpenAI, Key Vault, Azure Policy Experience with Self Hosting LLM Fine-tuning and prompt engineering for LLMs (e.g., GPT, Gemini, Claude) Secure deployment of LLMs via APIs with input/output filtering and logging Integration of LLMs into RAG pipelines, document intelligence, and agentic workflows Use of vector databases (e.g., FAISS, Pinecone, Chroma More ❯

Oversight Translate business requirements into technical specifications; review solution architecture and ensure alignment with best practices. Guide teams working with JavaScript (Node.js/React), cloud platforms (AWS/Azure/GCP), and data formats (JSON, XML, ANSI X12, EDIFACT). Vendor & Stakeholder Management Select and manage external vendors/SIs; negotiate contracts and SLAs. Facilitate communication between … Integration: EDI (ANSI X12, EDIFACT), REST/GraphQL APIs, OAuth2, Webhooks Languages & Frameworks: JavaScript/TypeScript (Node.js, React), Python (for data/AI), SQL Cloud & DevOps: AWS/Azure/GCP services, CI/CD pipelines, Docker/Kubernetes AI/ML Tooling: Familiarity with cloud AI services (SageMaker, Vertex AI, Azure AI) and More ❯

4+ years’ experience across data engineering, data science, and data visualisation Proficiency in Python, SQL, R, and familiarity with relational databases (SQL Server, Oracle) Experience with cloud platforms (Azure or AWS), data formats (CSV, JSON, XML), and deployment tools (ADF, Azure ML) Strong data visualisation skills (Power BI, Tableau) and experience designing client-facing More ❯