251 to 275 of 698 MLOps Jobs in the UK

Code (IaC) to support data pipelines and processing workflows on AWS. Design and maintain systems for data version control and reproducible machine learning workflows (MLOps). Work closely with data scientists, analysts and engineers to translate analytical and operational requirements into effective data solutions. Contribute to a collaborative, multidisciplinary environment ...

Hadoop, Synapse) with clear cut-over and reconciliation plans Monitor and optimise DBU consumption and cluster policies, giving the client clear cost visibility Enable MLOps and GenAI use cases where in scope, including MLflow, Model Serving and Genie Act as trusted advisor to client stakeholders, running workshops, design authorities ...

assurance environments (e.g. financial services). An understanding of the latest AI safety research and active involvement in that community. Deep knowledge of modern MLOps practices, CI/CD, and large-scale deployments. A collaborative and supportive work environment The opportunity to have a high impact in a growing organisation ...

heavily regulated environments. Understanding of secure AI adoption, AI governance, and emerging AI security risks. Exposure to Data Science, Machine Learning Engineering, or MLOps environments. What's on Offer: Opportunity to work on cutting-edge AI and Machine Learning initiatives within a prominent financial institution. Long-term programme with strong ...

Strong experience across segmentation, propensity, lifetime value, personalisation or forecasting. Experience with large-scale behavioural, transactional or customer datasets. Understanding of production data science, MLOps and model monitoring. Commercial judgement and the ability to simplify complex technical findings. Desirable Experience providing technical leadership, peer review or coaching to other data ...

techniques to power systems analysis, curtailment modelling, constraint analysis and renewable energy optimisation. Prototype and deploy AI solutions using cloud technologies and modern MLOps practices where appropriate. Produce clear visualisations and technical insights for planning applications, investment decisions and stakeholder reporting. Continuously evaluate emerging AI technologies and identify opportunities ...

fast-moving, high-ownership, cross-functional team What you’ll bring to the role A background in Software Engineering, Data Engineering or MLOps Strong experience building scalable infrastructure or distributed systems in the cloud Solid understanding of how systems are deployed, scaled and secured Experience applying good engineering practice ...

reliable, repeatable, and scalable releases of AI systems, models, and data pipelines into production. Establish AI monitoring and observability strategy across InfraOps and MLOps, defining SLAs, SLOs, alerting, and performance/cost tracking, and driving continuous optimization. Integrate AI/ML systems into enterprise environments, ensuring interoperability, security, compliance ...

working within diverse teams. A passion for continuous learning and personal development, with a willingness to explore new ideas and approaches. Familiarity with MLOps (Machine Learning Operations) practices, including the deployment, monitoring, and maintenance of AI/ML models in production environments and experience with cloud platforms and deploying ...

loops, and technologies such as Gemini, Claude and OpenAI APIs. Hands‐on experience with AI tools/frameworks (e.g., Braintrust, AutoEval) and/or MLOps tools (e.g., Airflow, MLflow, Vertex AI, or similar). Solid understanding of data engineering practices, including ETL, batch/streaming pipelines, and data quality monitoring. ...

organizations or large‐scale strategic technology programs* Proven experience managing the full product engineering lifecycle using Agile methodologies with a focus on MLOps and CI/CD for AI* Extensive experience delivering solutions in cloud (AWS/Azure), IaaS, and PaaS environments, specifically leveraging cloud-native AI/ML services ...

agent frameworks , vector databases , and LLM orchestration tools . Ability to lead multi-disciplinary teams and manage complex AI projects. Advanced proficiency in Python , MLOps, and software engineering principles. Experience setting technical standards, governance frameworks , and performance benchmarks. Strong consulting mindset with the ability to translate emerging technology into business ...

release processes for ML or other production software systemsExperience deploying, serving and operating machine-learning models in production environments3-7 years’ professional experience in MLOps, ML platform engineering, ML infrastructure, backend engineering, DevOps or SREStrong understanding of observability, monitoring, alerting, incident response and common failure modes in ML systemsStrong production ...

company where our software platform enables trusted AI at scale. Services of the platform include data preprocessing, AI model fine-tuning, inference oversight and MLOps for AI solutions in production. For traditional enterprises that have an aspiration to leverage AI to disrupt their industries but lack the skills or capabilities ...

Awareness of data models in a Medalion Architecture Experience building Semantic, Metric or Analytic models Experience of building Machine Learning models Any experience in MLOps or operationalising Machine Learning Knowledge of Data Quality Frameworks in Python Qualifications Industry focused degree or equivalent working experience Azure certifications are desirable Developing Others ...

cross‐functional work collaborating with other teams. Strong communicator – able to explain complex technical concepts to different audiences. Experience in one or more of: MLOps for Kubernetes‐based clusters Building production systems with large language models Efficient computing based on low‐precision arithmetic. Experience writing C++/Triton/CUDA ...

cross‐functional work collaborating with other teams. Strong communicator – able to explain complex technical concepts to different audiences. Experience in one or more of: MLOps for Kubernetes‐based clusters Building production systems with large language models Efficient computing based on low‐precision arithmetic. Experience writing C++/Triton/CUDA ...

cross‐functional work collaborating with other teams. Strong communicator – able to explain complex technical concepts to different audiences. Experience in one or more of: MLOps for Kubernetes‐based clusters Building production systems with large language models Efficient computing based on low‐precision arithmetic. Experience writing C++/Triton/CUDA ...

Machine Learning Engineer or Data Scientist. Skills: Strong proficiency in Python and modern ML frameworks (PyTorch, TensorFlow).Experience with cloud infrastructure (AWS) and MLOps tools (Docker, Langchain) is a plus. Professional Mindset: Detail-oriented, innovative thinker with a passion in applied AI research and a commitment to collaboration. Why Join ...

loops, and technologies such as Gemini, Claude and OpenAI APIs. Hands-on experience with AI tools/frameworks (e.g., Braintrust, AutoEval) and/or MLOps tools (e.g., Airflow, MLflow, Vertex AI, or similar). Solid understanding of data engineering practices, including ETL, batch/streaming pipelines, and data quality monitoring. ...

cross-functional work collaborating with other teams. Strong communicator - able to explain complex technical concepts to different audiences. Experience in one or more of: MLOps for Kubernetes-based clusters Building production systems with large language models Efficient computing based on low-precision arithmetic. Experience writing C++/Triton/CUDA ...

cross-functional work collaborating with other teams. Strong communicator - able to explain complex technical concepts to different audiences. Experience in one or more of: MLOps for Kubernetes-based clusters Building production systems with large language models Efficient computing based on low-precision arithmetic. Experience writing C++/Triton/CUDA ...

frameworks such as TensorFlow/PyTorch. Proficiency with Python and strong software development background. Knowledge and experience with AWS is highly desirable. Experience with MLOps practices, including versioning, deployment, and monitoring of models highly desirable. Ability to communicate complex technical concepts clearly to non-technical stakeholders. Why Work for Proximie ...

Vault, cloud-native equivalents), OPA/policy-as-code, SBOM and SLSA concepts. Platform: Kubernetes, containers, Terraform, service mesh, observability stacks AI/ML: MLOps and LLMOps tooling, model registries, vector stores and retrieval architectures, evaluation frameworks, agent frameworks, AI gateway patterns Experience operating under model risk management (e.g. ...

with Engineering and Data colleagues to turn model outputs into reusable, scalable data assets rather than one-off analysis or tables . Partner with MLOps colleagues to deploy, monitor and retrain models, with clear ownership, versioning in MLflow and documented handover points. Turn complex model outputs into clear, commercially relevant ...