301 to 325 of 873 MLOps Jobs in the UK

engineering — SLIs/SLOs, incident management, cost and capacity management (incl. LLM token/credit cost control). Nice‐to‐have skills LLMOps/MLOps — model serving, gateway/proxy management, prompt/version management, guardrails at runtime. Experience hosting AI/agentic platforms as a shared internal service (multi ...

writing clean, efficient, and modular code suitable for production environments. Desirable Skills or Knowledge Familiarity with AMO physics or quantum machine learning. Experience with MLOps best practices. Knowledge of systems like Apache Kafka, MQTT or real‐time data pipelines. Experience with cloud platforms (AWS, Azure, GCP). Deep expertise ...

cost management Model serving and inference at production scale (eg KServe, RayServe, Triton, vLLM, or similar) with real latency and cost constraints(preferred RayServe) MLOps pipeline tooling - training pipelines, model registries, feature stores, and lineage (Kubeflow, MLflow, Feast, Weights & Biases, or equivalents) LLMOps in production - inference serving, prompt/version ...

following AI/ML frameworks: Huggingface, Torch, Tensforflow, Scikit-Learn, and SpacyExperience in of any of the following additional platforms related to MLOps: MLFlow, dbt, Docker, Kubernetes.Experience with working cloud environments such as AWSTechnical Concept RequirementsExperience in any of the following AI/ML topics within a work context: Natural ...

writing clean, efficient, and modular code suitable for production environments. Desirable Skills or Knowledge Familiarity with AMO physics or quantum machine learning. Experience with MLOps best practices. Knowledge of systems like Apache Kafka, MQTT or real-time data pipelines. Experience with cloud platforms (AWS, Azure, GCP). Deep expertise ...

PyTorch) Understanding of core ML concepts — model training, evaluation, and production trade-offs — enough to design robust interfaces around them Experience with DevOps and MLOps Degree-level qualification in computer science or related field Deep understanding of Python Familiarity with Linux, bash, and the command line Ability to write logical ...

OECD AI Principles, model risk management, or responsible AI frameworks. Experience with AI red teaming, model evaluation, bias testing, explainability tooling, monitoring tools, MLOps, LLMOps, or AI governance platforms. Experience advising on third-party AI tools, enterprise AI platforms, or AI-enabled vendor solutions. Certifications or advanced training ...

following AI/ML frameworks: Huggingface, Torch, Tensforflow, Scikit-Learn, and SpacyExperience in of any of the following additional platforms related to MLOps: MLFlow, dbt, Docker, Kubernetes.Experience with working cloud environments such as AWSTechnical Concept RequirementsExperience in any of the following AI/ML topics within a work context: Natural ...

optimisation and high‐security solutions for enterprise clients Expertise in implementing SSO across a variety of industry standard software Preferred/Bonus Experience with MLOps/LLMOps (Softwares such as Sagemaker, Kubeflow or ZenML). Deployment of on‐premise Kubernetes Prometheus (or other stacks) observability Experience with AWS Karpenter & Compute ...

following AI/ML frameworks: Huggingface, Torch, Tensforflow, Scikit-Learn, and Spacy* Experience in of any of the following additional platforms related to MLOps: MLFlow, dbt, Docker, Kubernetes.* Experience with working cloud environments such as AWSTechnical Concept Requirements* Experience in any of the following AI/ML topics within ...

development and deployment of ML and AI models to prove and deliver tangible commercial value. Act as a technical bridge between Data Science and MLOps to embed best practice deployment techniques across the team. Take hands-on ownership of big projects, working with a large, event-based data set. Research ...

development and deployment of ML and AI models to prove and deliver tangible commercial value. Act as a technical bridge between Data Science and MLOps to embed best practice deployment techniques across the team. Take hands-on ownership of big projects, working with a large, event-based data set. Research ...

subject matter expert regarding GCP’s latest ML/AI tooling, and continuously prototyping and advocating for new tooling to ensure that our MLOps and AI infrastructure remains fit for purpose. Collaborating with Platform Engineering and Product to prioritise relevant workstreams across the Beatport Group. Working in conjunction with ...

enterprise and industry-standard software platforms. A strong understanding of infrastructure security, reliability and operational best practice. Desirable Experience The following would be advantageous: MLOps or LLMOps experience. Experience with platforms such as SageMaker, Kubeflow or ZenML . Extensive on-premises Kubernetes deployment experience. Prometheus or comparable observability platforms. ...

retrieval systems. Familiarity with scientific, biomedical, or scholarly datasets. Experience with knowledge graphs, ontologies, or semantic enrichment systems. Exposure to production ML systems and MLOps practices. Academic or industry research experience in NLP, information retrieval, search, or generative AI. Experience working in content‐rich, knowledge‐intensive, or highly regulated domains. ...

right level of review and controls based on riskCollaborate with Cloud, Data, Networks, and Digital teams to ensure secure configuration of AI infrastructure, including MLOps and compute environmentsGuide programmes and product teams with clear, practical recommendations that balance security, delivery, and innovationDrive compliance with regulatory, legal, and internal frameworks (including ...

datasets (scientific, biomedical, or enterprise data)Familiarity with scientific ontologies and metadata standards (e.g., MeSH, UMLS, ORCID, CrossRef)Exposure to production ML systems and MLOps practicesFamiliarity with data visualization and analytical tooling (e.g., Tableau, Power BI, matplotlib, seaborn, or similar) to communicate insights effectivelyExperience with human-in-the-loop evaluation ...

cloud data warehousing principles. Expertise with cloud data warehouse solutions such as Databrick, Snowflake or Redshift. Proven experience in DataOps, CI/CD (MLOps is a plus) Exceptional written, verbal, and listening communication skills, with the ability to effectively explain complex technical concepts to both technical and non-technical audiences. ...

access expectations. Experience with PETs or privacy‐preserving ML frameworks such as Flower, Opacus, TensorFlow Federated or similar. Cloud platforms, containerisation, CI/CD, MLOps or production ML systems. Experience evaluating synthetic data using both utility and privacy metrics. Hiring Process We feel hiring should be transparent and give ...

SAP. Familiarity with the modern data stack and cloud data platforms across multiple hyperscalers. Comfort positioning AI solutions — Agentic AI, GenAI/RAG, MLOps, AI automation — to enterprise decision-makers. Experience with Database Managed Services or Infrastructure Managed Services sales cycles and pricing models. Background selling into $300M-$1B revenue ...

Databricks is seeking a Senior Specialist Solutions Architect for AI/ML in London. You will be the trusted technical expert for ML/AI, guiding customers and the Field Engineering team to design production ...

WinsAbove is seeking a Senior Specialist Solutions Engineer to act as a trusted technical expert in machine learning and AI. In this hybrid role based in London, you will guide customers in implementing production-grade ...

Hiscox is seeking an experienced Machine Learning Engineer to join a newly formed ML Engineering team. You will build and maintain infrastructure to deploy data‐driven models, and develop Python APIs to serve ML models ...

learning and predictive analytics through to cutting-edge Generative AI applications. You will develop production-ready AI solutions, contribute to the evolution of our MLOps capabilities and reusable accelerators, and help shape innovative proof-of-concepts and client proposals that showcase Envitia's AI expertise. Working within multidisciplinary teams … solutions to solve complex operational challenges. Developing scalable data pipelines and AI services that transform structured and unstructured data into actionable insights. Implementing MLOps practices to support model deployment, monitoring, governance and continuous improvement. Applying Natural Language Processing (NLP), predictive analytics and decision-support techniques to mission-critical use cases. ...

Machine Learning, Data Science, Statistics, Mathematics or another quantitative discipline. Experience building and deploying production-grade machine learning models, with a solid understanding of MLOps, Git and CI/CD practices. Strong Python programming skills, including experience with Pandas, Scikit-learn and either PyTorch or Keras/TensorFlow. Proven experience ...