201 to 225 of 1,027 MLOps Jobs in England

domains Expertise in model validation, explainability, governance and ethical AI principles Advanced proficiency in Python (e.g. Scikit-learn, TensorFlow/PyTorch) and SQL, plus familiarity with ML engineering and MLOps practices Nice to have: Experience in setting or influencing data science strategy in a growing organisation Familiarity with AWS SageMaker and modern cloud-based ML workflows History of publications, open More ❯

managing business-critical machine learning models using Azure ML in Production environments. Experience in data wrangling using Python, SQL and ADF. Experience in CI/CD and DevOps/MLOps and version control. Familiarity with data visualization and reporting tools, ideally PowerBI. Good written and verbal communication and interpersonal skills. Ability to convey technical concepts to non-technical stakeholders. Experience More ❯

including deep learning applications; C/C++ for computer vision, geometry processing, or scientific computing; software engineering concepts and best practices (e.g., versioning, testing, CI/CD, API design, MLOps); container-ization and orchestration (Docker, Kubernetes, Slurm); writing pipelines and experiment environments, including running experiments in pipelines in a systematic way. What we offer Be part of something larger: Make More ❯

clearly communicate and present to internal and external stakeholders. Nice to have, but not essential NLP/Deep learning experience (e.g. huggingface, spaCy) Deep learning framework experience (preferably PyTorch) MLOps experience (e.g. data and model versioning, model deployment CI/CD, MLFlow/DVC) Cloud platform experience, especially from an ML standpoint (AWS preferred) Statistical testing experience Experience with AWS More ❯

to AI/LLM projects Proficiency with modern AI/LLM tools and frameworks (e.g. PyTorch, HuggingFace, OpenAI, Mistral, Llama, etc.) Strong Python skills and familiarity with cloud platforms, MLOps, and enterprise tech stacks Experience framing customer problems and delivering impactful AI solutions in real-world settings Excellent communication and presentation skills, able to connect technical capabilities to business value More ❯

clearly communicate and present to internal and external stakeholders. Nice to have, but not essential NLP/Deep learning experience (e.g. huggingface, spaCy) Deep learning framework experience (preferably PyTorch) MLOps experience (e.g. data and model versioning, model deployment CI/CD, MLFlow/DVC) Some basic devops experience useful (kubectl, helm, etc.) Cloud platform experience, especially from an ML standpoint More ❯

e.g., Kafka, Spark Streaming). Proficiency in CI/CD pipelines for data deployment using Azure DevOps, GitHub Actions, or Terraform for Infrastructure as Code (IaC). Understanding of MLOps principles, including continuous integration (CI), continuous delivery (CD), and continuous training (CT) for machine learning models. Experience with performance tuning and query optimisation for efficient data workflows. Strong understanding of More ❯

pipelines using AWS Lambda, Step Functions, and API Gateway for real-time AI inference and automation. Familiarity with containerized AI deployments using Amazon EKS and AWS Fargate. DevOps and MLOps Expertise: Hands-on experience with CI/CD pipelines for AI/ML workflows using AWS CodePipeline, CodeBuild, and SageMaker Pipelines. Proficiency in monitoring and maintaining AI systems with Amazon More ❯

and SDLC concepts in development of an application. Preferred Skills and Experience: Have experience integrating Machine Learning solutions into production-grade software and have an understanding of ModelOps and MLOps principles Had previous exposure to Natural Language Processing (NLP) problems and have familiarity with key tasks such as Named Entity Recognition (NER), Information Extraction, Information Retrieval, etc. Can understand and More ❯

platforms such as OpenAI on Azure, AWS Bedrock, GCP Vertex AI, or Gemini AI. Architecture & Deployment: Designing, deploying, and scaling AI architectures aligned to enterprise standards. Proven experience in MLOps and AI lifecycle management, with scalable deployments across AWS, GCP, and Azure. Bridging business and technical teams, owning high- and low-level design for services, products, and solutions. Optimizing solutions More ❯

Software Development Engineer- Finance AI and ML Dev, PXT Finance - ML Forecasting and Core Engineering Amazon Finance Tech team leads innovation to combine data-driven finance with the AI approach driving accuracy, next gen forecasting capabilities, speed, efficiency, and reliability More ❯

Senior Data Scientist - Creative Optimization Join to apply for the Senior Data Scientist - Creative Optimization role at GroupM Senior Data Scientist - Creative Optimization 1 day ago Be among the first 25 applicants Join to apply for the Senior Data Scientist More ❯

Join to apply for the Senior Data Engineer (Databricks) role at DATAPAO Get AI-powered advice on this job and more exclusive features. This range is provided by DATAPAO. Your actual pay will be based on your skills and experience More ❯

relative to Marketing, Customer Insights, and Safer Gambling and establish a strong culture of data-driven decision-making in our organisation's strategy. We are looking for an experienced MLOps Engineer to support the delivery of ML products. You will work closely with the Data Science team to understand the data and product requirements. You will also collaborate with the More ❯

our team. Join us in shaping a workplace where proximity enhances collaboration while inclusivity strengthens our community. Skills and Experience Thorough knowledge of the R language Working understanding of MLOps and DevOps frameworks Daily use of GitHub, including version control, collaboration, testing and CI/CD Superb written and verbal communication skills anddemonstrated ability to effectivelycommunicate complex technical and statistical … ideas to non-specialists Experience in cloud platforms such as databricks What you will do Act as a bridge between statisticians and technical teams. Design and implement MLOps frameworks to support the deployment of statistical models as REST APIs. Refactor and optimise R code for production use, with a focus on performance, reproducibility, and API integration. Educate both statisticians and … engineering teams on MLOps principles to ensure shared understanding. Working at Ascent At Ascent we promote a healthy work-life balance by offering flexibility in where you work. We also promote well-being and provide access to Well Being Coaches. Your development and learning will be taken seriously, and we'll support your professional development with training and certification, with More ❯

relative to Marketing, Customer Insights, and Safer Gambling and establish a strong culture of data-driven decision-making in our organisation's strategy. We are looking for an experienced MLOps Engineer to support the delivery of ML products. You will work closely with the Data Science team to understand the data and product requirements. You will also collaborate with the More ❯

to complex business problems, with the goal of improving supply chain efficiency, optimise vehicle movement, and enhance operational workflows across the organisation. You’ll be supported by a modern MLOps and Data Engineering function, giving you the time and tools to focus on innovation , model development , and strategic delivery . Key Responsibilities Lead and mentor a data science team focused … mathematical optimisation techniques (e.g., Linear Programming , Scheduling , Graph Theory ) to complex business problems. Work cross-functionally with senior stakeholders to translate business requirements into scalable technical solutions. Collaborate with MLOps and Engineering teams to productionise models using robust and scalable pipelines. Champion the integration of model outputs into wider data and reporting platforms. Clearly communicate technical insights and model outcomes … functional squads. What You’ll Get in Return A leadership role where your work has direct and measurable impact on operational efficiency and bottom-line performance. Dedicated support from MLOps and Engineering teams to accelerate delivery. Access to career development support including coaching, mentoring, and leadership training . A competitive salary package including car allowance , bonus , and comprehensive benefits such More ❯

to complex business problems, with the goal of improving supply chain efficiency, optimise vehicle movement, and enhance operational workflows across the organisation. You’ll be supported by a modern MLOps and Data Engineering function, giving you the time and tools to focus on innovation , model development , and strategic delivery . Key Responsibilities Lead and mentor a data science team focused … mathematical optimisation techniques (e.g., Linear Programming , Scheduling , Graph Theory ) to complex business problems. Work cross-functionally with senior stakeholders to translate business requirements into scalable technical solutions. Collaborate with MLOps and Engineering teams to productionise models using robust and scalable pipelines. Champion the integration of model outputs into wider data and reporting platforms. Clearly communicate technical insights and model outcomes … functional squads. What You’ll Get in Return A leadership role where your work has direct and measurable impact on operational efficiency and bottom-line performance. Dedicated support from MLOps and Engineering teams to accelerate delivery. Access to career development support including coaching, mentoring, and leadership training . A competitive salary package including car allowance , bonus , and comprehensive benefits such More ❯

to complex business problems, with the goal of improving supply chain efficiency, optimise vehicle movement, and enhance operational workflows across the organisation. You’ll be supported by a modern MLOps and Data Engineering function, giving you the time and tools to focus on innovation , model development , and strategic delivery . Key Responsibilities Lead and mentor a data science team focused … mathematical optimisation techniques (e.g., Linear Programming , Scheduling , Graph Theory ) to complex business problems. Work cross-functionally with senior stakeholders to translate business requirements into scalable technical solutions. Collaborate with MLOps and Engineering teams to productionise models using robust and scalable pipelines. Champion the integration of model outputs into wider data and reporting platforms. Clearly communicate technical insights and model outcomes … functional squads. What You’ll Get in Return A leadership role where your work has direct and measurable impact on operational efficiency and bottom-line performance. Dedicated support from MLOps and Engineering teams to accelerate delivery. Access to career development support including coaching, mentoring, and leadership training . A competitive salary package including car allowance , bonus , and comprehensive benefits such More ❯

team will design and deploy advanced models that improve supply chain efficiency, optimise vehicle movement, and enhance operational workflows across the organisation. You’ll be supported by a modern MLOps and Data Engineering function, giving you the time and tools to focus on innovation , model development , and strategic delivery . This is a hybrid role , with flexibility to work from … mathematical optimisation techniques (e.g., Linear Programming , Scheduling , Graph Theory ) to complex business problems. Work cross-functionally with senior stakeholders to translate business requirements into scalable technical solutions. Collaborate with MLOps and Engineering teams to productionise models using robust and scalable pipelines. Champion the integration of model outputs into wider data and reporting platforms. Clearly communicate technical insights and model outcomes … functional squads. What You’ll Get in Return A leadership role where your work has direct and measurable impact on operational efficiency and bottom-line performance. Dedicated support from MLOps and Engineering teams to accelerate delivery. Access to career development support including coaching, mentoring, and leadership training . A competitive salary package including car allowance , bonus , and comprehensive benefits such More ❯

Experience developing AI/ML solutions using Python? * Knowledge of frameworks such as PyTorch (preferred), TensorFlow, or Scikit-learn? * Experience with NLP, deep learning, or computer vision? * Familiarity with MLOps tools (Azure ML Pipelines, MLflow, Docker, Kubernetes)? * Experience working with cloud platforms such as Azure, GCP, or AWS? * The abbility to engage with technical and non-technical teams? Would you … prospects and a strong benefits package, including hybrid working, bonus schemes, private healthcare and more? If so, please apply! Python | AI | Machine Learning | NLP | Deep Learning | Azure | PyTorch | TensorFlow | MLOps | Kubernetes | OpenAI | CI/CD | Software Engineering | LegalTech All of our opportunities require that applicants are eligible to work in the specified country/location, unless otherwise stated in the More ❯

ready to design, deploy, and maintain production-grade Machine Learning systems. You're willing to champion best practices in code quality, testing, observability, and MLOps. You have experience with MLOps tools and practices (CI/CD, Docker, Kubernetes) and cloud platforms (GCP, AWS, or Azure). You're a smart, intense, and focused individual willing to build things efficiently in … platform needs (including NLP and OCR). Optimize AI models and associated systems for performance, scalability, and cost-effectiveness in a production environment. Implement and manage the infrastructure for MLOps, including fine-tuning, deployment, monitoring, and versioning. Develop robust data pipelines for ingestion, cleaning, model training, and continuous deployment. Build retrieval-aware repositories for model training, evaluation, and real-time More ❯

impact projects that span our entire organisation. As part of our ambitious 2027 strategy, you’ll join a growing Data Science team focused on implementing modern data science and MLOps standards while upholding ethical and responsible practices. In this leadership role, you’ll be responsible for delivering AI and ML solutions that drive measurable business outcomes, while mentoring others and … to develop impactful, ethical AI solutions. Act as a thought leader and data evangelist, sharing knowledge across Bupa’s global data science community and promoting best practices in AI, MLOps, and responsible innovation. Ensuring full compliance with regulatory frameworks and standards relevant to the health insurance sector (e.g., GDPR, DPA) as well as proactively aligning Bupa’s Responsible AI Framework. … or Snowflake. Demonstrated experience delivering end-to-end AI and GenAI projects, including model design, development, deployment, and monitoring in production environments. Strong understanding of cloud-native ML infrastructure, MLOps practices, and scalable architecture design. Excellent communication and stakeholder management skills, with the ability to influence and collaborate across technical and non-technical teams. Experience working in an agile environment More ❯

Have hands-on experience with LLMs , ML/DL frameworks like PyTorch, TensorFlow, LangChain Know how to deploy, monitor & optimise ML models in real-world systems Are comfortable with MLOps tooling (CI/CD, Docker, Kubernetes) & cloud platforms (GCP/AWS/Azure) Want to build first-of-its-kind AI infrastructure with a lean, focused, high-performing team Love … building smart, scalable tech that makes a massive impact What you’ll do: Build production-grade AI/ML systems (NLP, OCR, LLM-based) Develop and manage robust MLOps pipelines and infrastructure Optimise models for performance, scalability, and cost Deploy observability tools (OpenTelemetry, Grafana) Collaborate with software engineers to embed AI into the product using APIs Create real-time, context 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 Troubleshoot and debug user issues Provide operational and user-facing documentation We are looking for a Senior Platform Engineer More ❯