101 to 125 of 417 MLOps Jobs in the UK

Experience integrating AI models into production systems using GCP, AWS, or Azure. Familiarity with vector databases, embedding models, or retrieval-augmented generation (RAG). Knowledge of Docker, Airflow, or MLOps pipelines. Strong understanding of AI ethics, data privacy, and responsible model deployment. TO BE CONSIDERED... Please either apply online or email me directly at .By applying for this role, you More ❯

stacks (TypeScript, Node.js, Go, or similar) Strong understanding of ML principles and model evaluation Experience with cloud-based model deployment (GCP preferred) Familiarity with containerised workflows (Docker, serverless) and MLOps tools (MLflow, Vertex AI, SageMaker) Excellent communication and collaboration skills in a remote-first team Willingness to travel occasionally for in-person collaboration or client work Nice to Have Experience More ❯

stacks (TypeScript, Node.js, Go, or similar) Strong understanding of ML principles and model evaluation Experience with cloud-based model deployment (GCP preferred) Familiarity with containerised workflows (Docker, serverless) and MLOps tools (MLflow, Vertex AI, SageMaker) Excellent communication and collaboration skills in a remote-first team Willingness to travel occasionally for in-person collaboration or client work Nice to Have Experience More ❯

Demonstrated experience working with large-scale health, genomic, or biobank datasets (e.g. UK Biobank, All of Us, Our Future Health). Exposure to production deployment and model lifecycle management (MLOps awareness a plus). Strong communicator with the ability to operate between science and engineering teams. Nice to Have Experience integrating multi-omic or imaging data with clinical outcomes. Knowledge More ❯

Demonstrated experience working with large-scale health, genomic, or biobank datasets (e.g. UK Biobank, All of Us, Our Future Health). Exposure to production deployment and model lifecycle management (MLOps awareness a plus). Strong communicator with the ability to operate between science and engineering teams. Nice to Have Experience integrating multi-omic or imaging data with clinical outcomes. Knowledge More ❯

performance and manage end-to-end ML lifecycle (data ingestion, training, evaluation, deployment). Mentor junior engineers and contribute to code reviews, best practices, and technical decision-making. Implement MLOps pipelines for continuous training, deployment, and monitoring of models. Ensure compliance with data privacy and security regulations (GDPR, etc.). Required Skills & Qualifications: Bachelor's or Master's degree in … Solid understanding of ML algorithms , NLP , deep learning , and statistical methods. Experience with Docker, Kubernetes , and cloud platforms like AWS/Azure/GCP . Hands-on experience with MLOps tools (MLflow, SageMaker, Kubeflow, etc.) and version control systems. Strong knowledge of APIs, microservices architecture, and CI/CD pipelines. Proven experience in leading teams, managing stakeholders, and delivering end More ❯

Communicate complex concepts to all stakeholders. At least 3 years of experience in AI solution engineering. Large Language Models experience including prompt engineering and RAG implementations. Expert data analytics, MLOps practices and API development. Desirable knowledge in Docker and Kubernetes More ❯

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 ❯