76 to 100 of 119 MLOps Jobs in England

initiatives. Working for a US Sports analytics client you'll collaborate with their technical team, providing advanced mathematical models derived from large datasets and statistics for the client's MLOps team to productionise. Location/WFH: You'll join a friendly and sociable team in the London office two days a week (Mondays and Thursdays) with flexibility to work from More ❯

will use your skills to: Tune machine learning methods to best leverage our state-of-the-art processing capabilities Deploy and maintain machine learning methods in a DevOps/MLOps based machine learning environment Create robust high-quality code using test-driven development (TDD) techniques and adhering to the SOLID coding standards Your work will enable sustained improvements to products … Head of Data Science, and Head of Technical Underwriting Propose, proof-of-concept, develop, and deliver novel machine learning processes that automate current manual processes, and leverage DevOps and MLOps software. Work in a collaborative environment with data science to help deploy machine learning methods that are state-of-the-art, robust, and future extensible. Tune machine learning methods for … of the following predictive modelling techniques; Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets and Clustering Experience in DevOps and Azure ML, or other MLOps and ML Lifecycle technology stacks, such as AWS, Databricks, Google Cloud, etc. Experience with deploying services in Docker and Kubernetes Experience in creating production grade coding and SOLID programming principles More ❯

large (AI) transformational journeys BCG does for its clients. Often involves the following engineering disciplines : Cloud Engineering Data Engineering (not building pipelines but designing and building the framework) DevOps MLOps/LLMOps Often work with the following technologies : Azure, AWS, GCP Airflow, dbt, Databricks, Snowflake, etc. GitHub, Azure DevOps and related developer tooling and CI/CD platforms, Terraform or … other Infra-as-Code MLflow, AzureML or similar for MLOps; LangSmith, Langfuse and similar for LLMOps The difference to our "AI Engineer" role is: Do you "use/consume" these technologies, or are you the one that "provides" them to the rest of the organization. What You'll Bring TECHNOLOGIES: Programming Languages: Python Experience with additional programming languages is a More ❯

Job Title: ML Ops/LLM Ops Engineer Location: Hybrid (potentially 1 day per week in east London) Contract: 6 month Contract Day Rate: £400 per day (Outside IR35) About the Role We are seeking an experienced ML Ops/ More ❯

initiatives. Working for a US Sports analytics client you'll collaborate with their technical team, providing advanced mathematical models derived from large datasets and statistics for the client's MLOps team to productionise. Location/WFH: You'll join a friendly and sociable team in the London office two days a week (Mondays and Thursdays) with flexibility to work from More ❯

initiatives. Working for a US Sports analytics client you'll collaborate with their technical team, providing advanced mathematical models derived from large datasets and statistics for the client's MLOps team to productionise. Location/WFH: You'll join a friendly and sociable team in the London office two days a week (Mondays and Thursdays) with flexibility to work from More ❯

initiatives. Working for a US Sports analytics client you'll collaborate with their technical team, providing advanced mathematical models derived from large datasets and statistics for the client's MLOps team to productionise. Location/WFH: You'll join a friendly and sociable team in the London office two days a week (Mondays and Thursdays) with flexibility to work from More ❯

cloud data. Build end-to-end data pipelines : collect sim/tele-op logs, manage versioned data lakes, apply weak supervision, curate datasets, and run evaluation loops. Collaborate with MLOps and Data Platform teams to scale distributed training and optimise models for real-time deployment . Hire, mentor, and lead a high-calibre team of research scientists and engineers. What More ❯

diverse modeling techniques, including tree based models, advanced neural networks and hybrid models. ** Skilled in optimisng ML for real time serving think quantization, pruning, and distillation. ** Proficient with modern MLOps practices and tooling, handling everything from model governance to scalable deployment pipelines. ** Comfortable working hands on with Python, GPU acceleration, and distributed computing frameworks. ** A confident communicator and collaborator, able More ❯

diverse modeling techniques, including tree based models, advanced neural networks and hybrid models. ** Skilled in optimisng ML for real time serving think quantization, pruning, and distillation. ** Proficient with modern MLOps practices and tooling, handling everything from model governance to scalable deployment pipelines. ** Comfortable working hands on with Python, GPU acceleration, and distributed computing frameworks. ** A confident communicator and collaborator, able More ❯

Tesco, Sainsbury's, O2, Halifax, AA, Saga and Lloyds Bank to list a few. As a Machine Learning Engineer, you will help build and maintain the pricing team's MLOps and ML Lifecycle environment to support the creation of pipelines by automating the sophisticated machine learning models and processes that underpin our market-leading technical modelling and pricing function. Key … Responsibilities: Build an MLOps/DevOps environment to support machine learning automation Build the pipelines that automate the regular model update and monitoring processes Build a framework that supports the creation, deployment, maintenance, and monitoring elements that non-data scientist and machine learning analysts produce, including assisting with hyper-parameter tuning, feature engineering, feature selection, and validation, reporting and visualisation … and communication processes. Work closely with the data science team to integrate modelling approaches and techniques Key Skills and Experience: Previous experience as a DevOps/MLOps engineer Experience in Azure ML or databricks, or similar industry approved technology stack (i.e. AWS, Kubernetes and Docker, Google Cloud) Understanding of machine learning models and the modelling process, from data ingestion and More ❯

will help managethe ML lifecycle fromdata selection and collection, ML model design and creation all the way through tooperationalizationand monitoring. You will work closely with data scientists and senior MLOps Engineers to understand and implement models into production. At Data Reply, you'll enjoy extensive training opportunities coupled with a detailed learning pathto guide you along the way.You'll thrive … learning models to production Implement solutions to monitorthe performance of Machine Learning models in production over time Work in teams with other technical experts, e.g. Data Engineers, Data scientists, MLOps Engineers, Data Visualization Specialists Interact with domain experts from different industries to understand and tackle challenging problems Explore and understand client datain relation to the problem you're tackling andcommunicate More ❯

ML solutions to ensure safety, reliability, and compliance. Advise teams on ethical, regulatory, and operational compliance , integrating AI governance into project delivery. Support safe deployment of AI systems, guiding MLOps best practices and risk mitigation strategies. Candidate Requirements: Active SC clearance (DV desirable). Deep technical expertise in AI/ML , including hands-on experience with model development, deployment, and More ❯

experience applying these techniques in production environments. Project Leadership : Proven experience leading complex technical projects, with a track record of successfully evolving existing systems and innovating with new solutions. MLOps & Modern Practices : Strong understanding of modern data science and MLOps practices, including model lifecycle management, experimentation, and CI/CD. Core Programming & Software Craftsmanship : Proficiency in Python and SQL, with More ❯

MLOps Engineer Our trusted partner, which operates within the Ed-Tech domain, employs over 10,000 individuals across 100 countries and has a reach of 600 million users, is recruiting an MLOps Engineer who has Chatbot (Voice) integration project experience using Python, Pytorch, Pyspark and AWS LLM/Generative AI. Our client is paying £400 PD Outside IR 35 to More ❯

our client's data team. This is a hands-on role where you'll design and build robust data pipelines, transform ML prototypes into production-ready systems, and champion MLOps best practices across the business. As a Machine Learning Engineer, you'll play a crucial role in ensuring our clients' data and AI strategy scales effectively, directly influencing the way … to-end data pipelines and feature engineering workflows. Deploying and monitoring ML models in production using tools such as MLflow, Vertex AI, or Azure ML. Driving best practices in MLOps, including CI/CD, experiment tracking, and model governance. Supporting the data warehouse and ensuring data quality, governance, and accessibility. Collaborating with cross-functional teams to deliver trusted datasets and More ❯

enable the building and maintenance of our AI systems. Our teams make extensive use of open source technologies such as, Kubernetes, Kubeflow, KServe, Argo, Buildpacks, and other cloud-native MLOps technologies. From technical governance to upstream collaboration, we are committed to enhancing the impact and sustainability of open source. Join the AI Group as a Senior ML Platform Engineer and … workflows, pinpoint, and resolve inefficiencies, and to inform the next set of features for the platforms Collaborate with open-source communities and AI application teams to build a cohesive MLOps experience Design CI/CD automation frameworks that incorporate regulatory requirements Develop cloud-native deployment patterns for AI systems across environments Troubleshoot and debug user issues Provide operational and user More ❯

Unitary's future. Take ownership of customer outcomes with the autonomy to make decisions that surprise and delight our customers. Contribute full-stack development including software engineering, DevOps, and MLOps, along with light task and project management to ensure your AI solutions deliver maximum value. We are looking for someone who is as excited about Unitary's mission as we … better, but not essential, if you have: Experience working in a fully remote, international team Previous startup experience A background in building and operating agentic AI systems Experience with MLOps practices and tools, and monitoring machine learning systems in production Knowledge of CI/CD practices and tools such as GitLab CI, Argo CD Proficiency with SQL and NoSQL databases More ❯

Unitary's future. Take ownership of customer outcomes with the autonomy to make decisions that surprise and delight our customers. Contribute full-stack development including software engineering, DevOps, and MLOps, along with light task and project management to ensure your AI solutions deliver maximum value. You We are looking for someone who is as excited about Unitary's mission as … better, but not essential, if you have: Experience working in a fully remote, international team Previous startup experience A background in building and operating agentic AI systems Experience with MLOps practices and tools, and monitoring machine learning systems in production Knowledge of CI/CD practices and tools such as GitLab CI, Argo CD Proficiency with SQL and NoSQL databases More ❯

Role? Shape and deliver the security architecture strategy for enterprise cloud and AI/ML programmes. Work on cutting-edge initiatives in the financial services domain, integrating AI and MLOps with security guardrails. Act as a trusted advisor to senior leadership , influencing both business and technology direction. Key Responsibilities Define and evolve security architecture strategies for cloud, AI/ML … and MLOps environments . Act as a senior security advisor to leadership, engineering, and business stakeholders. Develop security architecture standards, patterns, and guidelines for enterprise solutions, with specific coverage for AI/ML workloads. Conduct security architecture reviews, threat modelling, and risk assessments for AI/ML systems and pipelines . Ensure solutions comply with European financial services regulations (GDPR … PSD2, DORA, NIS2) as well as emerging AI governance frameworks (e.g., EU AI Act, NIST AI RMF). Integrate security into DevSecOps and MLOps pipelines , including CI/CD and infrastructure-as-code environments. Drive adoption of Zero Trust principles, encryption standards, IAM policies, and network/data/application security controls. Collaborate with data scientists, ML engineers, and IT More ❯

needs, and see the real-world impact of your work. What You'll Be Doing Building and deploying production ML pipelines in cloud environments (AWS, Azure, or GCP) Implementing MLOps best practices to maintain and scale AI applications Working directly with NHS trusts and healthcare clients to understand their challenges Contributing to both project delivery and the development of repeatable … learning algorithms and their practical application Ability to deliver high-quality work to tight deadlines Genuine interest in healthcare - you want your work to matter Highly Desirable: Experience with MLOps in cloud environments Background in healthcare, consulting, or research settings Exposure to modern cloud platforms (AWS/Azure/GCP) Salary: £40,000 - £55,000 + good benefits + bonus More ❯

Technical Product Manager - Data, GCP, BigQuery, Cloud, Pyton, CI/CD, MLOps Role Profile Role Title: Technical Product Manager (Dynamic Allocation Services) Reporting To: Head of Product Location: Birmingham/Remote (with occasional travel to customer sites) Summary The Technical Product Manager (Dynamic Allocation Services) is responsible for driving the technical direction, development, and optimisation of our product. Combining product … design into technical specifications. Experience designing or managing decision-support systems, simulations, or optimisation engines. Familiarity with cloud environments (e.g. GCP, BigQuery) and modern deployment practices (CI/CD, MLOps). Product & Delivery Skills Ability to translate complex technical concepts into structured product requirements. Experience in Agile product delivery, backlog management, and sprint planning. Up to 10% discretionary bonus Fully More ❯

principles and standards Translating business objectives into AI/ML delivery plans, managing cross-functional teams to execute against them. Supporting clients in scaling AI/ML capabilities, including MLOps, cloud infrastructure, and data readiness, as well as transition from on-prem to modern cloud-based infrastructures (AWS, Azure, GCP) Leading the end-to-end delivery of AI/ML … out the required roadmap of initiatives for an organisation to transform to become more data-driven Expertise in AI/ML technologies, including supervised/unsupervised learning, NLP, LLMs, MLOps, and cloud-based AI platforms (Azure, AWS, GCP) Ability to shape and articulate compelling value propositions for AI initiatives Experience supporting large-scale AI programmes or portfolios, including stakeholder engagement More ❯

easier for coaches and athletes at any level to capture video, analyze data, share highlights and more. Ready to join us? Your Role We're looking for a Senior MLOps Engineer to join our team and deliver new experiences and valuable insights to our coaches, athletes and fans. You'll help us build and deploy game-changing initiatives that use … cutting-edge computer-vision and deep learning at scale to shape the future of sports at every level, from professional teams to local high schools. As a Senior MLOps Engineer, your priorities will include: Delivering for customers at scale. Optimise and deploy ML models and systems on both cloud and edge environments, scaling to thousands of simultaneous sports matches. Leading More ❯

Machine Learning Operations Engineer - Remote - 50- 70k + excellent benefits We're looking for a skilled Machine Learning Operations Engineer to join a newly established team working on an exciting data platform project. This is a hands-on role where More ❯