351 to 375 of 581 MLOps Jobs in London

Financial Services environmentsConfidence operating across multiple workstreams while building sustainable AI and analytics capability within teamsBonus Points ForHands-on experience with AI product development, MLOps, model lifecycle management or AI platform engineeringKnowledge of responsible AI, model risk management, AI governance or ethical AI frameworksExperience supporting AI strategy, roadmap definition ...

client outcomes.Bonus Points ForExperience supporting business development, proposition development or pre-sales activities within a consulting environment.Hands-on familiarity with modern data science, MLOps, AI operationalisation or cloud-native analytics platforms.Knowledge of responsible AI, AI governance, model risk management or enterprise analytics operating models.Experience supporting organisational change, business analysis ...

lead large-scale, interdisciplinary initiatives in complex, regulated environments. Understanding of the software product development lifecycle; ideally including AI/ML lifecycle, model governance, MLOps, and responsible AI frameworks. Strong leadership, stakeholder engagement, and communication skills. Familiarity with audit processes, information security, and ethical AI implementation are all a strong ...

outcomes. Bonus Points ForExperience supporting business development, proposition development or pre-sales activities within a consulting environment. Hands-on familiarity with modern data science, MLOps, AI operationalisation or cloud-native analytics platforms. Knowledge of responsible AI, AI governance, model risk management or enterprise analytics operating models. Experience supporting organisational change ...

latency requirements without compromising model performance Write clean, well-tested, well-documented code and uphold engineering standards across the team Lead model handovers to MLOps engineers, with thorough documentation covering capabilities, known limitations, failure modes and retraining criteria Stay current with advances in ML engineering, distributed training and biomedical ...

Solution Providers and have set the architectural direction for complex, full-stack AI platforms spanning multiple organisations.You have deep expertise in containerisation, orchestration, and MLOps at scale, and have established the standards others follow.You have a proven track record of developing senior engineering talent, coaching leads and managers, building capability ...

commerce, or subscription-based products. Experience working with large-scale data using PySpark or equivalent distributed data processing tools. Familiarity with production environments, MLOps, or data pipelines. Benefits: Discretionary bonus opportunityPrivate Medical InsuranceDental Scheme25 days holiday per yearOn Site GymSubsidised CaféFree soft drinksOn site barAccess to cycle garage and showersPlease ...

technical advisory, translating complex infrastructure trade-offs into clear, defensible recommendations tied to business outcomes. Define monitoring, observability, and reliability strategy across InfraOps and MLOps, and implement the instrumentation, SLAs, SLOs, and cost/performance governance for production AI/ML systems. Ensure enterprise integration, security, compliance, and regulatory alignment ...

teams own the full delivery lifecycle, from early ideas through to production systems that create measurable impact for our customers and the business. As MLOps Engineering Manager, you will help shape how we build, deploy and operate machine learning products at scale, working closely with ML Engineers, Data Engineers, Software … Engineers, Data Scientists, Product Managers and stakeholders across Trainline.In this role as the MLOps Engineering Manager, you will... Build and lead a new team of MLOps Engineers, creating an environment where people can do their best work while delivering meaningful outcomes for customers and the business.Define and evolve MLOps processes ...

defence, government, and national security.Working alongside Data Scientists, Software Engineers, and AI specialists, you'll take projects from experimentation through to production, leveraging modern MLOps and LLMOps practices on AWS to build scalable, secure AI systems.What You'll Be DoingDesign, develop, and deploy machine learning models for traditional … using modern AI frameworks.Lead experimentation cycles, defining hypotheses, running evaluations, and iterating on models before production deployment.Develop robust ML pipelines using AWS services and MLOps tooling.Implement experiment tracking, model versioning, monitoring, and reproducibility best practices.Build feature engineering pipelines and contribute to feature store development.Monitor production models, optimise performance, and drive ...

create measurable impact. You're comfortable working across the full AI deployment lifecycle from use case discovery and solution architecture to multimodal agent development, MLOps pipeline implementation, and production optimization. You understand what makes agents perform well in production and how to systematically improve quality through observability and evaluation. Experience … custom SDKs (Python, TypeScript) Act as trusted technical advisor to customers, shaping AI strategy and guiding roadmap decisions from concept to production Data Strategy & MLOps Infrastructure Design data architectures with efficient processing pipelines and ingestion workflows for training and inference on aion's platform Implement RAG systems with vector databases ...

programs; Collaborate with data engineers, clinicians, and business teams to tailor solutions to client needs; Deploy AI and machine learning models in production using MLOps and LLMOps practices; Use cloud platforms and data solutions to ensure scalability and operational integrity; Present data-driven recommendations to senior audiences and demonstrate … real‐world datasets; Familiarity with NLP and deep learning techniques applied to biomedical data; Knowledge of Azure, AWS, or GCP and model deployment using MLOps frameworks; Strong Python and SQL programming skills, with experience in PyTorch, TensorFlow, and Hugging Face; Experience with Databricks, Spark, and other data platforms ...

environments and bare-metal local hardware. API Development: Create high-performance, asynchronous REST and WebSocket APIs using FastAPI to serve real-time conversational agents. MLOps & Infrastructure CI/CD Automation: Design automated machine learning pipelines for model testing, versioning, and continuous deployment. Containerization: Pack applications using Docker or Podman … SageMaker), Azure (Azure ML), and GCP (Vertex AI). CI/CD Tools: Experience with GitLab CI, GitHub Actions, Jenkins, or specialized MLOps platforms (e.g., Kubeflow, MLflow). Preferred Qualifications Conversational Context: Experience with dialogue management, prompt engineering, and Retrieval-Augmented Generation (RAG). Data Analytics: Familiarity with real-time ...

software code development Builds engineering stack required for Data and AIML products, including data engineering, backend engineering, Cloud infra DevOps and MLOps Designs and implements data engineering solutions, leveraging modern big data technologies Drives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery … experience developing Production-scale Cloud-native data engineering solutions in commercial environments Familiarity with Cloud Data engineering services (e.g., ETL, Glue, S3, Athena) and MLOps stack Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, code review, test acceleration ...

Data Science, who owns AI/ML and data governance direction at ComplyAdvantage. Your remit is execution: the architectural design of our company-wide MLOps and agentic AI platforms, the build-out of new models and agent systems, and the engineering bar across all of it. You will also represent … financial crime a thing of the past. Scope of the roleScope & Key ResponsabilitiesArchitectural Leadership: Lead the architectural design and implementation of our company-wide MLOps and agentic AI platforms, covering training, evaluation, serving, feature/vector stores, and agent orchestration. Strategic Execution: Translate the ML and agentic AI roadmaps ...

systems tailored to audit applications. Contribute to architectural decisions and solution governance. Write clean, efficient, and scalable code that adheres to software engineering principles, MLOps practices, and cloud-native development. AI Solution Delivery: Own the implementation of ML pipelines, APIs, and data integration workflows. Operational Excellence: Contribute to defining reusable … development patterns, enforcing coding standards, and implementing MLOps best practices that support version control, performance optimisation, and maintainability. Cross-Disciplinary Collaboration: Work side-by-side with data scientists, product managers, platform engineers, and QA teams to align on technical requirements, delivery timelines, and integration plans. Provide hands-on contributions ...

domains like customer service, document automation, summarization, and knowledge retrieval. Fine-tune or adapt foundation models using domain-specific data. Collaborate with data engineers, MLOps, and product teams to build end-to-end AI applications and APIs. Develop custom prompts and prompt chains using tools like LangChain, LlamaIndex, PromptFlow … workflows and deploy them via APIs or web apps (e.g., FastAPI, Streamlit, Flask). Familiarity with cloud platforms (AWS/GCP/Azure) and MLOps best practices. Excellent communication skills with the ability to translate technical solutions into business impact. Skills and Personal attributes we would like to have: Experience ...

designing and building APIs, distributed systems, and event-driven architectures in modern programming languages such as Python, TypeScript, Java, Go, or similar Familiarity with MLOps practices, model monitoring, observability, versioning, and automated deployment pipelines preferred Strong problem-solving skills with the ability to navigate ambiguity, experiment rapidly, and deliver impactful … cost efficiency while supporting increasing AI adoption and usage Implement engineering best practices around observability, monitoring, testing, security, and operational excellence Establish and champion MLOps practices including model lifecycle management, prompt versioning, automated evaluation, and continuous improvement Build reusable frameworks, developer tooling, and platform capabilities that accelerate AI innovation across ...

part of the Data and AI platform team; you’ll get to pioneer on real world problems, bringing your knowledge of AI/ML, MLOps and LLMs to bear - collaborating cross team to make your vision a reality. You’ll be backed by our platform team, and have a wealth … scientific evaluation with the operational maturity to champion high-value applications and confidently push back on unsuitable AI use cases. Design, refine and build MLOps component of the data and AI platform, from Vector Databases through feature stored and model serving, all at the millisecond scale. Implement CI/ ...

## AI EngineerApplylocations: Kings Cross, Londontime type: Full timeposted on: Posted 11 Days Agojob requisition id: UMG-25167Music is Universal It’s the passionate and dedicated team at Universal Music who help make us the ...

Shape the Future of AI & Data with UsAt Datatonic, we are Google Cloud's premier partner in AI, driving transformation for world-class businesses. We push the boundaries of technology with expertise in machine learning ...

Basic information Location London Business Line Technology & Transformation Job Type Permanent/FTC Date published 17-Aug-2026 Req # 23589 Job description Connect to your IndustryDo you want to be at the heart of ...

Basic information Location London Business Line Tax & Legal Job Type Permanent/FTC Date published 19-Aug-2026 Req # 22446 Job description Connect to your IndustryDeloitte’s Tax Digital Innovation team is a key ...

teams own the full delivery lifecycle, from early ideas through to production systems that create measurable impact for our customers and the business. As MLOps Engineering Manager, you will help shape how we build, deploy and operate machine learning products at scale, working closely with ML Engineers, Data Engineers, Software … Engineers, Data Scientists, Product Managers and stakeholders across Trainline. Responsibilities Build and lead a new team of MLOps Engineers, creating an environment where people can do their best work while delivering meaningful outcomes for customers and the business. Define and evolve MLOps processes, tooling and infrastructure choices across the technology ...

Databricks seeks a senior technologist to architect production-grade ML and AI workloads, spanning end-to-end pipelines, training/inference optimization, and MLOps lifecycle management with cloud-native integration. You will lead GenAI initiatives, advise solution architects during pre-sales and post-sales cycles, influence the AI roadmap ...