101 to 125 of 370 MLOps Jobs in England

as an AI/ML professional. A strong understanding of Python programming concepts, leading practices, and SQL skills. Experience in any cloud computing environment. Familiarity with Machine Learning Operations (MLOps) methodologies. An eye for detail and strong analytical skills. Excellent problem-solving abilities. Strong communication and presentation skills Primary Skills : 1. Problem Solving - Defines a problem, generates solutions, and evaluates More ❯

AI You'll have Strong engineering background with experience deploying production-grade AI or ML systems Skilled in Python or similar languages, with exposure to modern AI frameworks and MLOps Experience working in cloud-native environments (Kubernetes, Terraform, CI/CD) Comfortable engaging with clients, solving real-world technical challenges, and leading by example Experience leading teams This is an More ❯

AI You'll have Strong engineering background with experience deploying production-grade AI or ML systems Skilled in Python or similar languages, with exposure to modern AI frameworks and MLOps Experience working in cloud-native environments (Kubernetes, Terraform, CI/CD) Comfortable engaging with clients, solving real-world technical challenges, and leading by example Experience leading teams This is an More ❯

/CD, build/release pipelines, and automation Exposure to containers and orchestration (Docker, Kubernetes, ECS/AKS) Experience with monitoring/observability Interest in AI, ML pipelines, or MLOps (experience highly beneficial but not essential) Someone who enjoys ownership, autonomy and working in a small, smart engineering team Why it’s a great move High-impact role working directly More ❯

/CD, build/release pipelines, and automation Exposure to containers and orchestration (Docker, Kubernetes, ECS/AKS) Experience with monitoring/observability Interest in AI, ML pipelines, or MLOps (experience highly beneficial but not essential) Someone who enjoys ownership, autonomy and working in a small, smart engineering team Why it’s a great move High-impact role working directly More ❯

natural problem solver with curiosity for cutting-edge tools and frameworks Desirable Experience Experience delivering AI or ML solutions in a commercial or consultancy setting Knowledge of data engineering, MLOps, or automation workflows Previous experience engaging directly with clients and senior stakeholders Why Join This is an opportunity to join a fast-scaling AI business at a defining stage of More ❯

natural problem solver with curiosity for cutting-edge tools and frameworks Desirable Experience Experience delivering AI or ML solutions in a commercial or consultancy setting Knowledge of data engineering, MLOps, or automation workflows Previous experience engaging directly with clients and senior stakeholders Why Join This is an opportunity to join a fast-scaling AI business at a defining stage of More ❯

environments (e.g. AWS, GCP, or Azure) Exposure to modern data tools such as Airflow, dbt, or Snowflake Experience or strong interest in streaming technologies like Apache Kafka Interest in MLOps and modern data engineering best practices Why join: You’ll be part of a company with a clear mission and strong data culture, joining a team that values learning, collaboration More ❯

environments (e.g. AWS, GCP, or Azure) Exposure to modern data tools such as Airflow, dbt, or Snowflake Experience or strong interest in streaming technologies like Apache Kafka Interest in MLOps and modern data engineering best practices Why join: You’ll be part of a company with a clear mission and strong data culture, joining a team that values learning, collaboration More ❯

and ability to work cross-functionally. Desirable MSc/PhD in Machine Learning, Computer Vision, or related field. Knowledge of Generative AI models (GANs, diffusion, LLMs). Experience with MLOps and lifecycle management. Experience in startups or fast-paced R&D. Why apply? Flexible hybrid working (London office) A chance to shape the future of AI in sport and human More ❯

and ability to work cross-functionally. Desirable MSc/PhD in Machine Learning, Computer Vision, or related field. Knowledge of Generative AI models (GANs, diffusion, LLMs). Experience with MLOps and lifecycle management. Experience in startups or fast-paced R&D. Why apply? Flexible hybrid working (London office) A chance to shape the future of AI in sport and human More ❯

deployment of predictive and optimisation models across multiple industries Own the end-to-end ML pipeline: data exploration, feature engineering, modelling, evaluation, and deployment Collaborate with data engineers and MLOps professionals to ensure scalable, production-grade solutions Conduct rigorous A/B testing and performance measurement to validate impact Act as a technical lead within project teams, mentoring mid-level More ❯

deployment of predictive and optimisation models across multiple industries Own the end-to-end ML pipeline: data exploration, feature engineering, modelling, evaluation, and deployment Collaborate with data engineers and MLOps professionals to ensure scalable, production-grade solutions Conduct rigorous A/B testing and performance measurement to validate impact Act as a technical lead within project teams, mentoring mid-level More ❯

findings into actionable insights for coaches, analysts, and execs Highly Desirable Skills Football Analytics Experience : Familiarity with football-specific datasets (event, tracking, positiona l), and libraries like mplsoccer Advanced MLOps & Modelling : Experience with the Vertex AI ecosystem, especially pipelines, and advanced techniques such as player valuation , tactical modelling , etc. Bayesian Modelling : Knowledge of probabilistic programming (e.g., PyMC ) for uncertainty-aware More ❯

findings into actionable insights for coaches, analysts, and execs Highly Desirable Skills Football Analytics Experience : Familiarity with football-specific datasets (event, tracking, positiona l), and libraries like mplsoccer Advanced MLOps & Modelling : Experience with the Vertex AI ecosystem, especially pipelines, and advanced techniques such as player valuation , tactical modelling , etc. Bayesian Modelling : Knowledge of probabilistic programming (e.g., PyMC ) for uncertainty-aware More ❯

ML models. Partner with data engineers, ML engineers, architects, and business teams to shape ML initiatives. Present insights clearly through strong data visualisation and storytelling. Uphold software engineering and MLOps best practices (testing, versioning, quality, automation). Contribute to governance, responsible model usage, and data quality standards. Mentor juniors and support code reviews. Required Experience You’ll need: Strong Python More ❯

ML models. Partner with data engineers, ML engineers, architects, and business teams to shape ML initiatives. Present insights clearly through strong data visualisation and storytelling. Uphold software engineering and MLOps best practices (testing, versioning, quality, automation). Contribute to governance, responsible model usage, and data quality standards. Mentor juniors and support code reviews. Required Experience You’ll need: Strong Python More ❯

ML models. Partner with data engineers, ML engineers, architects, and business teams to shape ML initiatives. Present insights clearly through strong data visualisation and storytelling. Uphold software engineering and MLOps best practices (testing, versioning, quality, automation). Contribute to governance, responsible model usage, and data quality standards. Mentor juniors and support code reviews. Required Experience You'll need: Strong Python More ❯

solutions. Exposure to field services management or workforce management in regulated or safety-critical industries (utilities, energy, construction, etc.) is highly desirable. Exposure to machine learning/AI systems, MLOps and how data is leveraged for insights. Exposure to cloud infrastructure (AWS, GCP) and understanding of scalable architectures. Experience in solution architecture or as a technology consultant is a strong More ❯

data privacy, handling of sensitive data (e.g. GDPR) and data lineage • Knowledge of the DataOps processes for the continuous deployment of UCDAs to production environments • Data Science machine learning (MLOps) model lifecycle • Worked with modern lakehouse and data management platforms – e.g.Databricks, Atlan, Monte Carlo What you’ll get in return: At easyJet, we pride ourselves on a vibrant and inclusive More ❯

data privacy, handling of sensitive data (e.g. GDPR) and data lineage Knowledge of the DataOps processes for the continuous deployment of UCDAs to production environments Data Science machine learning (MLOps) model lifecycle Worked with modern lakehouse and data management platforms – e.g.Databricks, Atlan, Monte Carlo What you'll get in return: At easyJet, we pride ourselves on a vibrant and inclusive More ❯

Azure platform. You will work closely with data scientists, researchers, and product managers to translate complex analytical models into production-ready, scalable applications. Your expertise in Azure AI services, MLOps, and data engineering will be crucial in delivering high-impact AI capabilities. Responsibilities • Design & Development: Architect and develop end-to-end AI/ML solutions using Azure AI services (e.g. … Azure Machine Learning, Azure Cognitive Services, Azure Databricks, Azure Synapse Analytics). • Model Deployment & Management: Implement robust MLOps practices for continuous integration, continuous delivery (CI/CD), monitoring, and retraining of machine learning models in Azure. • Data Pipelining: Build and optimize scalable data pipelines for ingesting, transforming, and preparing large datasets for AI model training and inference. • Performance Optimization: Optimize … Documentation: Create comprehensive documentation for AI solution architectures, deployment procedures, and operational guidelines. • Stay Current: Keep abreast of the latest advancements in Azure AI services, machine learning technologies, and MLOps trends. Qualifications we seek in you! Minimum Qualifications • Bachelor's or master’s degree in computer science, Engineering, Data Science, or a related quantitative field. • Relevant years of experience in More ❯

Azure platform. You will work closely with data scientists, researchers, and product managers to translate complex analytical models into production-ready, scalable applications. Your expertise in Azure AI services, MLOps, and data engineering will be crucial in delivering high-impact AI capabilities. Responsibilities • Design & Development: Architect and develop end-to-end AI/ML solutions using Azure AI services (e.g. … Azure Machine Learning, Azure Cognitive Services, Azure Databricks, Azure Synapse Analytics). • Model Deployment & Management: Implement robust MLOps practices for continuous integration, continuous delivery (CI/CD), monitoring, and retraining of machine learning models in Azure. • Data Pipelining: Build and optimize scalable data pipelines for ingesting, transforming, and preparing large datasets for AI model training and inference. • Performance Optimization: Optimize … Documentation: Create comprehensive documentation for AI solution architectures, deployment procedures, and operational guidelines. • Stay Current: Keep abreast of the latest advancements in Azure AI services, machine learning technologies, and MLOps trends. Qualifications we seek in you! Minimum Qualifications • Bachelor's or master’s degree in computer science, Engineering, Data Science, or a related quantitative field. • Relevant years of experience in More ❯

Engineering Manager, MLOps, Marketplace, Ecommerce, | 35 Million Users | UK Remote OR London, Hybrid, 1 Day PW, Up to £140,000 About the Company Our client is an extremely well know, digital marketplace focused on sustainable ecommerce. With over 35 million of active users globally, they’re redefining how people buy and sell second-hand fashion, aiming to make the future … The organisation champions diversity, equal opportunity, and flexible working. They offer a progressive benefits package designed to support wellbeing, learning, and work-life balance. The role of Engineering Manager, MLOps, Marketplace, Ecommerce, | 35 Million Users | UK Remote OR London, Hybrid, 1 Day PW, Up to £140,000 Our Client is looking for an experienced MLOps Engineering Manager to lead and … scale their MLOps function. You will be shaping how machine learning is developed, deployed, and scaled across the organisation. This is a genuinely high-impact role: you’ll lead a talented team of 6-8 engineers, set the strategic direction for ML infrastructure, and ensure the business continues to deliver reliable, scalable, and high-performing ML systems that drive real More ❯

Engineering Manager, MLOps, Marketplace, Ecommerce, | 35 Million Users | UK Remote OR London, Hybrid, 1 Day PW, Up to £140,000 About the Company Our client is an extremely well know, digital marketplace focused on sustainable ecommerce. With over 35 million of active users globally, they’re redefining how people buy and sell second-hand fashion, aiming to make the future … The organisation champions diversity, equal opportunity, and flexible working. They offer a progressive benefits package designed to support wellbeing, learning, and work-life balance. The role of Engineering Manager, MLOps, Marketplace, Ecommerce, | 35 Million Users | UK Remote OR London, Hybrid, 1 Day PW, Up to £140,000 Our Client is looking for an experienced MLOps Engineering Manager to lead and … scale their MLOps function. You will be shaping how machine learning is developed, deployed, and scaled across the organisation. This is a genuinely high-impact role: you’ll lead a talented team of 6-8 engineers, set the strategic direction for ML infrastructure, and ensure the business continues to deliver reliable, scalable, and high-performing ML systems that drive real More ❯