476 to 500 of 603 MLOps Jobs in England

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

issues early and keep things running smoothly Troubleshooting complex issues across distributed systems, spanning data infrastructure, training, and inference Continuously improving our data and MLOps practices, and helping shape the roadmap for how our platform evolves as we scale What you'll need Strong proficiency in Python and SQL, with … quality practices (validation, cleaning, normalisation) and/or production-grade observability Ability to design resilient, scalable architectures, and comfort operating and troubleshooting distributed systems MLOps experience, for example model serving, experiment tracking, GPU/distributed training optimisation, or reproducible ML workflows A self-starter mentality: comfortable identifying problems and driving ...

Platform Strategy & Architecture: Assess, define and evolve enterprise AI platform architectures, covering LLM and agentic frameworks, AI gateways, model lifecycle management, data platforms, MLOps/LLMOps foundations and integration patterns. Support clients in evaluating build, buy and hybrid approaches aligned to business needs, risk appetite and operational requirements.• AI Platform … operating cloud-native, platform engineering, AI platform or reliability engineering solutions within complex enterprise environments. • Strong understanding of AI platform architectures including LLMOps, MLOps, agentic AI frameworks, model lifecycle management and AI operational controls. • Experience establishing and scaling SRE practices including observability, SLIs, SLOs, error budgets, incident management and reliability ...

Platform Strategy & Architecture: Assess, define and evolve enterprise AI platform architectures, covering LLM and agentic frameworks, AI gateways, model lifecycle management, data platforms, MLOps/LLMOps foundations and integration patterns. Support clients in evaluating build, buy and hybrid approaches aligned to business needs, risk appetite and operational requirements.• AI Platform … operating cloud-native, platform engineering, AI platform or reliability engineering solutions within complex enterprise environments. • Strong understanding of AI platform architectures including LLMOps, MLOps, agentic AI frameworks, model lifecycle management and AI operational controls. • Experience establishing and scaling SRE practices including observability, SLIs, SLOs, error budgets, incident management and reliability ...

At Elanco (NYSE: ELAN) – it all starts with animals! As a global leader in animal health, we are dedicated to innovation and delivering products and services to prevent and treat disease in farm animals and ...

We're looking for a hands-on, generalist data scientist to own ML across all parts of our broad business, including Membership, Food & Beverage, Operations, Digital and Events. As Lead Data Scientist, you'll be ...

Join JPMorgan Corporate Investment Bank's industry-leading data analytics team, where you'll combine cutting-edge machine learning techniques with unique data assets to optimize business decisions. As an Applied AI & Machine Learning Associate ...

Company Description Depop is the community-powered circular fashion marketplace where anyone can buy, sell and discover desirable secondhand fashion. With a community of over 35 million users, Depop is on a mission to make ...

Thehumanoid is hiring a Senior Dev/MLOps Engineer to join their Data & Compute Platform team in London. This role involves managing the lifecycle of ML models and infrastructure, building CI/CD pipelines, ensuring system reliability and security, and collaborating with cross-functional teams. Candidates should have strong Python ...

from data pipelines to model deployment, collaborating with platform and backend engineers to scale production systems. Applicants should have 5+ years in ML/MLOps, strong Python, Databricks experience, and familiarity with AWS or Azure. #J-18808-Ljbffr ...

more excellent minds to challenge the status-quo and help it reach new horizons. Where you come in? We're looking for a Senior MLOps Engineer to join our Algorithmic Underwriting team. In this role, you’ll develop and extend our MLOps system, empowering our underwriting algorithm to improve effectively … efficiently. We'll work together across the business to tackle exciting technical challenges that go far beyond traditional MLOps systems. For instance, you’ll expand our MLOps system to manage the lifecycle of actuarial models and rules-based models alongside standard machine learning models. You’ll also have the opportunity ...

modern architectures: Medallion Lambda Kappa Experience building or contributing to cloud-based data platforms AWS preferred Familiarity with: S3 Glue Athena Data Science & MLOps Exposure to: data analysis MLOps feature engineering Curiosity and willingness to go deeper in these areas Why you’ll love it here We want to make ...