551 to 575 of 707 MLOps Jobs in the UK

customers. They will be subject matter experts in the areas of Predicative AI, Machine Learning, Generative AI along with associated capabilities in areas like MLops, Data Pipelines, and DevOps. The role will interface directly with the customers' business, data science and IT Operations teams to establish CDW credibility and position … learning, lab time and formal training. What you will do Position CDW Custom AI capabilities - Engage with all Customer AI personas: technical personas (CDO, MLOps, AI/ML Engineer, Data Scientist), outcome-driven personas (CEO, CTO, LOB) and ITDMs (CIO, VP Infrastructure). Technical SME on CDW Custom AI – Maintain ...

customers. They will be subject matter experts in the areas of Predicative AI, Machine Learning, Generative AI along with associated capabilities in areas like MLops, Data Pipelines, and DevOps. The role will interface directly with the customers' business, data science and IT Operations teams to establish CDW credibility and position … learning, lab time and formal training. What you will do Position CDW Custom AI capabilities - Engage with all Customer AI personas: technical personas (CDO, MLOps, AI/ML Engineer, Data Scientist), outcome-driven personas (CEO, CTO, LOB) and ITDMs (CIO, VP Infrastructure). Technical SME on CDW Custom AI – Maintain ...

Depop is looking for a Machine Learning Engineer to join the Ranking team in the UK. You will work alongside ML Scientists, Backend Engineers, MLOps, and other ML Engineers to build, deploy, maintain, and monitor the machine learning systems that power personalised ranking across key surfaces of the Depop … product teams to define integration requirements and coordinate deployment of ranking services. Help extend the ML infrastructure for ranking systems in collaboration with the MLOps team, including: Reproducible model training workflows CI/CD pipelines for model deployment Real-time and batch model serving Online/offline feature consistency through ...

Azure-based data and AI platform. This is hands‐on infrastructure and platform work – you'll be writing Terraform, designing network architecture, implementing MLOps (AI model) pipelines, and establishing DevSecOps patterns that engineering teams can use. This isn't a “thought leadership” or “strategy” role. … maintain CI/CD for Databricks notebooks, jobs, and infrastructure Work with data engineers on performance optimization, cost control, and platform capabilities MLOps & AI Platform (20%) Build ML model deployment pipelines using Azure ML, Databricks MLflow, or both Implement model versioning, experiment tracking, and model registry patterns Establish inference endpoints ...

including generative AI and agentic systems, on cloud infrastructure. You will own end-to‐end delivery from problem framing and experimental design through scalable MLOps, evaluation, governance, and integration with strategic systems. You will help set technical direction, establish reusable patterns, and ensure solutions are reliable, secure, and observable … reliability, incident management, and continuous improvement Strong Python software engineering skills, including modular object‐oriented design, testing, performance tuning, and debugging Working knowledge of MLOps and LLMOps and distributed systems, including training and serving patterns, batch versus real‐time architectures, feature stores, orchestration, and scalable data processing Ability to design ...

lifecycle — assessing client needs and data, selecting and customizing models (including Deep Learning, Generative AI, and Large Language Models), designing scalable data and DevOps & MLOps pipelines for training and production, and ensuring quality, value, and reliability of deployed systems. THE WORK Formulate real-world problems into practical, efficient, and scalable … Develop and implement machine learning algorithms, models, and computational systems; design and build scalable data pipelines to support model training and production with DevOps & MLOps Customize and apply Deep Learning and Gen AI models for various use cases based on the business needs, data availability, system and infrastructure requirements - including ...

concurrent projects, mitigating risk before it reaches delivery. Define LLM integration and prompting strategies, including RAG, fine‐tuning, evaluation, and guard‐railing approaches. Establish MLOps and LLMOps practices that ensure solutions are observable, testable, and production ready. Set architectural standards, reusable patterns, and reference implementations that raise the quality … 10+, with a track record of production deployments. Deep expertise in LLMs, agent frameworks (e.g. LangGraph, AutoGen, Semantic Kernel), API design, and orchestration. Proven MLOps/LLMOps capability — CI/CD for models, monitoring, evaluation, and cost optimisation. Hands‐on software engineering background (Python and modern tooling) underpinning your architectural ...

communicate complex findings to both technical and executive stakeholders. Key Responsibilities Design, implement and evolve a multi-omics AI platform, incorporating full-lifecycle MLOps Identify, ingest, link and curate data across large-scale multi-omics and imaging datasets, including data quality, validation, traceability and storage optimisation Standardise and automate … experience in a fast-paced environment, preferably a startup, with the ability to iterate, experiment, and deliver solutions efficiently. Practical experience across the entire MLOps lifecycle for cloud, hybrid and on-premise deployments. Adaptability and comfort working with evolving requirements and changing priorities, approaching new challenges with curiosity and openness. ...

Deloitte is seeking an experienced MLOps Engineer for a contract role in London, hybrid 3/4 days in client office. You will design, develop and deploy production-ready AI agents and scalable ML pipelines in a regulated financial services environment. The role covers Generative AI, retrieval systems, and enterprise ...

Booksy is seeking a Senior ML/MLOps Engineer to join their Data Science & Applied AI team. The role is fully remote and involves collaborating closely with Data Scientists to transition ML models from prototype to production. Responsibilities include overseeing the ML workflow and ensuring performance within SLAs. Ideal candidates ...

About Unifeye Unifeye is a delivery-led, Databricks-first consultancy helping organisations unlock the full value of their data and AI. We're a lean, high-growth team based in London, working at the intersection ...

This job is with Capgemini, an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. CAPGEMINI INVENT At Capgemini Invent, we ...

Junior DevOps/MLOps Engineer We are looking for a Junior DevOps/MLOps Engineer to help build, automate and maintain the infrastructure and pipelines that deliver software and machine learning models into production. Working alongside software and AI engineers, you will support reliable deployments, improve automation and help ensure …/CD tool. Linux administration and Docker containers. Infrastructure as code, such as Terraform or AWS CloudFormation. Exposure to model versioning, experiment tracking or MLOps tools. Experience using GitHub Copilot. What You Will Contribute You will help create repeatable deployment processes, reduce manual work and improve the reliability of software ...

currently seeking an MLOps AI Lead & Databricks Platform Specialist to join a global end client, taking ownership of the Databricks platform and supporting the delivery of robust, scalable MLOps capabilities. We are ideally looking for someone on a permanent basis , although contract-to-permanent could also be considered. Location: Hybrid … onsite in London, Covent Garden/Milton Keynes. Experience required: 3 – 5 years’ experience Proven experience managing data/analytics platforms and/or MLOps capabilities in a complex enterprise environment. Hands-on experience operating Databricks (workspace administration, cluster policies, jobs, Delta Lake, Unity Catalog, access controls, and production support ...

promote best practice across Data & AI Operations. Lead continuous improvement, including optimising long-running data pipelines and operational processes. Support DataOps, AIOps and MLOps activities across the team. Oversee the operational monitoring and governance of AI solutions, including emerging agentic AI capabilities. Support the implementation and ongoing optimisation of Databricks … enthusiasm for emerging AI technologies. It would be great if you also had Experience with Databricks. Experience with Azure or AWS. Exposure to MLOps or AI Operations. Experience with Power Apps or the wider Power Platform. Experience in financial services. At Royal London, you’ll be part of a mutual ...

responsible for turning machine learning models into production-grade solutions that deliver real value across the business. Working at the intersection of software engineering, MLOps, and data science, you'll build the frameworks, pipelines, and services that enable machine learning models to be deployed, monitored, scaled, and embedded within customer … one. Key responsibilities Partner with Data Scientists to transition models from experimentation into scalable, production-ready applications and services Design, build, and maintain MLOps frameworks, deployment pipelines, and automated model lifecycle processes Develop and support CI/CD pipelines, version control frameworks, and automated testing processes for machine learning solutions ...

Engine behind the Syrup platform and Anaplan’s forecasting solutions. The team is responsible for the production execution of forecasting and predictive models, the MLOps infrastructure supporting our data scientists, and the data processing services that deliver insights to enterprise customers. This role reports to the Director of Engineering … implement scalable, fault-tolerant predictive intelligence services and features as a core contributor to the ML Engine backend. Lead the technical implementation of MLOps capabilities, including model training pipelines, deployment workflows, and runtime infrastructure for production ML. Partner with data scientists to productionize models and graduate experimental work into stable ...

solution lifecycle — assessing client needs and data, selecting and customizing models (including Deep Learning, Generative AI, and Large Language Models), designing scalable data and MLOps/LLMOps pipelines for training and production, and ensuring quality, value, and reliability of deployed systems. THE WORK Formulate real-world problems into practical, efficient … Develop and implement machine learning algorithms, models, and computational systems; design and build scalable data pipelines to support model training and production with DevOps & MLOps Customize and apply Deep Learning and Gen AI models for various use cases based on the business needs, data availability, system and infrastructure requirements - including ...

Strong problem-solving, communication, and collaboration skills, with the ability to convey design choices and communicate effectively with stakeholders Familiarity with Machine Learning Operations (MLOps) Hands‐on experience using enterprise‐authorized AI‐assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated … development Familiarity with relational databases (e.g., Postgres) and AWS services such as S3, EKS, SageMaker, and Bedrock Practical experience with Kubernetes, EKS, Docker, Kafka, MLOps and Large Language Model Operations (LLMOps) Experience working on AIML systems and/or prior experience collaborating with data scientists #J-18808-Ljbffr ...

solution lifecycle — assessing client needs and data, selecting and customizing models (including Deep Learning, Generative AI, and Large Language Models), designing scalable data and MLOps/LLMOps pipelines for training and production, and ensuring quality, value, and reliability of deployed systems. THE WORK Formulate real-world problems into practical, efficient … Develop and implement machine learning algorithms, models, and computational systems Design and build scalable data pipelines to support model training and production with DevOps & MLOps Customize and apply Deep Learning and Gen AI models for various use cases based on the business needs, data availability, system and infrastructure requirements - including ...

business stakeholders to identify opportunities for optimization, forecasting, automation and intelligent decision support. Support the deployment of machine learning models into production environments using MLOps practices. Work with structured, semi-structured and streaming data to generate actionable insights; Contribute to AI-enabled solutions including Generative AI, Agentic AI, NLP, forecasting … Data Scientists and other analytical specialists to translate analytical approaches into production solutions. Experience developing production-grade user experiences and data visualizations. Experience with MLOps platforms and model lifecycle management. Familiarity with optimization, forecasting and simulation techniques. Experience building or contributing to AI-enabled operational products. Exposure to Generative ...

business stakeholders to identify opportunities for optimization, forecasting, automation and intelligent decision support. Support the deployment of machine learning models into production environments using MLOps practices. Work with structured, semi-structured and streaming data to generate actionable insights; Contribute to AI-enabled solutions including Generative AI, Agentic AI, NLP, forecasting … Data Scientists and other analytical specialists to translate analytical approaches into production solutions. Experience developing production-grade user experiences and data visualizations. Experience with MLOps platforms and model lifecycle management. Familiarity with optimization, forecasting and simulation techniques. Experience building or contributing to AI-enabled operational products. Exposure to Generative ...

functional agile team and owning the successful launches and ongoing operations of high-profile products in production. This is a senior software engineering/MLOps role focused on building and operating production services and platform capabilities, not a model research role. Data science experience is valuable but secondary to production … engineers and data scientists, mentor teammates, and drive continuous improvement and knowledge sharing. What you’ll bring 5+ years as an software engineer, MLOps Engineer, or similar, with hands-on production experience operating backend services or ML-backed APIs Proven expertise deploying ML models as production services, API design ...

functional agile team and owning the successful launches and ongoing operations of high‐profile products in production. This is a senior software engineering/MLOps role focused on building and operating production services and platform capabilities, not a model research role. Data science experience is valuable but secondary to production … engineers and data scientists, mentor teammates, and drive continuous improvement and knowledge sharing. What you’ll bring 5+ years as an software engineer, MLOps Engineer, or similar, with hands‐on production experience operating backend services or ML‐backed APIs Proven expertise deploying ML models as production services, API design ...

solutions. Acting as a key technical leader and cross-functional integrator, the Senior AI Platform Engineer partners with research, product, infrastructure, data engineering, and MLOps teams to design and operate the platforms required to train, evaluate, deploy, and govern large-scale AI systems across IQVIA products and healthcare use cases. … driving technology selection, migration strategies, performance optimisation, and integration with AI workflows. Serve as the primary technical coordination point across AI Research, Data Engineering, MLOps, Product, and Infrastructure teams, resolving dependencies and prioritising activities critical to delivery. Provide technical leadership for vendor selection, procurement, and technology partnerships, advising on compute ...