1 to 25 of 67 MLOps Jobs in the South East

identification and shaping of future AI opportunities once the first use cases have demonstrated value. Desirable skills: Azure AI Foundry and Azure Machine Learning. MLOps practices and tools such as MLflow. Containerisation and orchestration using Docker and Kubernetes. Experience developing copilots, AI agents or multi-step AI workflows. Experience working ...

deployments CI/CD experience with a focus on production ownership and reliability Understanding of data quality, testing and lineage best practices Desirable skills: MLOps or production machine learning experience Terraform, Ansible or other Infrastructure as Code tools PostgreSQL and modern data platforms Experience within Defence, National Security or regulated ...

technical stakeholders. Desirable Experience The following would be advantageous: Multimodal AI and reasoning. Edge or offline AI deployments. Kubernetes, particularly EKS or OpenShift. MLOps, including model evaluation, monitoring and reproducibility. Observability for agentic AI systems, including model performance, agent behaviour and drift. Agent orchestration and inter-agent communication protocols such ...

machine learning, and generative AI technologies to deliver innovative business solutions. Continuously improve platform performance, scalability, and operational efficiency while supporting AI governance and MLOps best practices. Unfortunately we are unable to progress with candidates that require sponsorship at this time Skills we would love you to have Experience working ...

Head of Engineering and Technical Architect Cloud & Platform Integration: Partner closely with our GCP and Data Engineering teams to build seamless LLMOps/MLOps CI/CD pipelines, ensuring scalable and cost‐effective model deployment via Vertex AI and containerized environments. Take ownership of building and maintaining robust LLMOps pipelines ...

machine learning, and generative AI technologies to deliver innovative business solutions. Continuously improve platform performance, scalability, and operational efficiency while supporting AI governance and MLOps best practices. Skills we would love you to have Experience working with Snowflake, including SQL development, data modelling, orchestration, and integration management. Experience with Azure ...

governance practices: PII handling, access control, and GDPR basics Nice to Have: RAG architecture, hybrid retrieval strategies, or prompt engineering experience Nice to Have: MLOps or ML pipeline experience Nice to Have: Domain knowledge in compliance, tax technology, or e-invoicing Due to client contractual obligations, the successful candidate will ...

governance practices: PII handling, access control, and GDPR basics Nice to Have: RAG architecture, hybrid retrieval strategies, or prompt engineering experience Nice to Have: MLOps or ML pipeline experience Nice to Have: Domain knowledge in compliance, tax technology, or e-invoicing Due to client contractual obligations, the successful candidate will ...

technical designs throughout the project lifecycle. Experience with large-scale data initiatives, data labelling strategies, synthetic data generation and data quality management. Familiarity with MLOps practices and cloud platforms for AI deployment. Experience working with academic partners, research institutions, grant-funded programmes or collaborative research consortia. Experience contributing to bids ...

secure deployments, including air‐gapped, on‐premises or sovereign cloud environments. Strong technical ownership, documentation and stakeholder communication skills. Desirable Kubernetes, EKS or OpenShift. MLOps, monitoring, evaluation and reproducibility. Agent orchestration, A2A or MCP. Multimodal, edge or offline AI deployments. Secure‐by‐design principles, including ISO 27001, NIST or OWASP. ...

frameworks. Azure AI Foundry, Azure OpenAI, Azure Machine Learning, Databricks, or equivalent cloud platforms. Data visualisation and storytelling tools such as Power BI. MLOps and model lifecycle management. Preferred Qualifications Experience in client-facing consulting roles. Exposure to cloud-based AI and analytics platforms. Understanding of Responsible AI and governance ...

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 practices Familiarity with data visualization and analytical tooling (e.g., Tableau, Power BI, matplotlib, seaborn, or similar) to communicate insights effectively Experience with human ...

data‐driven systems in production or near‐production settings. Experience with generative AI systems, LLM‐enabled applications or evaluation pipelines. Experience with cloud platforms, MLOps tooling, model serving or platform engineering. Advanced use of Linux, Docker, version control, CI/CD and service‐oriented deployment practices. Experience working across ...

data platform technologies and governance concepts, including metadata, lineage, cataloguing and access control. Experience delivering solutions in a regulated or controlled environment. Experience with MLOps, AI evaluation, monitoring and the operational support of AI solutions. Knowledge of containerisation, orchestration and API-first architecture. Familiarity with responsible AI, model governance ...

machine learning solutions in a data-rich commercial environment. Experience supporting operational, financial, customer or commercial decision-making through data and AI. Exposure to MLOps, MLflow or model lifecycle management. Experience with Microsoft Azure, Fabric or AI technologies. Job Offer Lead AI/ML Engineer Competitive salary ...

advanced AI, and specifically: The management of people, process, documentation associated with the development, deployment, maintenance, training and operational management of Machine Learning solutions (MLOps) The management of people, process, documentation, maintenance and operational management of Generative AI solutions (GenAIOps/LLMOps) Manage, objectively assess and track Technology Readiness Levels ...

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 ...

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. ...

support real-time conversational AI applications. Deploying machine learning workloads across AWS, Azure, GCP and on-premise/bare-metal infrastructure . Designing automated MLOps and CI/CD pipelines covering model testing, versioning, deployment and monitoring. Containerising AI applications using Docker or Podman and supporting consistent deployment across development … ideally including both ASR and TTS models. Experience deploying, serving or optimising Large Language Models or Small Language Models . Strong understanding of production MLOps , model deployment and CI/CD practices. Experience with container technologies including Docker and/or Podman . Practical cloud experience across one or more ...

Head of Engineering and Technical Architect Cloud & Platform Integration: Partner closely with our GCP and Data Engineering teams to build seamless LLMOps/MLOps CI/CD pipelines, ensuring scalable and cost-effective model deployment via Vertex AI and containerized environments. Take ownership of building and maintaining robust LLMOps pipelines. … data warehouse architectures. Hands-on experience with Google Cloud Platform (GCP) services including Vertex AI, BigQuery, Cloud SQL, and Google Cloud Storage (GCS). MLOps/LLMOps Pipelines: Proven track record of architecting pipelines for model deployment, performance tracking, hyperparameter tuning, and containerized workflows using Docker and Kubernetes (GKE/ ...

infrastructure Desirable attributes Hands-on experience building LLM-based systems Experience testing non-deterministic systems Understanding of statistics and inferential methods LangGraph, RAG, MCP, MLOps, IaaC, AWS What we offer Some of the benefits we include are: Private Medical Insurance Dental Insurance Parental Support Salary-Exchange Pension Employee Assistance Programme ...

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 ...

/CD, automated testing). Hands-on experience delivering AI or machine learning solutions at scale, including model development, deployment, and ongoing operations (MLOps). Experience with large language models (LLMs), generative AI techniques, or agentic AI frameworks applied to real-world business problems. Track record of managing multi-stakeholder ...

with governance. You will collaborate with stakeholders, promote best practices in SQL, Python, data modelling and AI development, and drive adoption of AI and MLOps to deliver innovative #J-18808-Ljbffr ...

series and experimental design Strong Python, including pandas, NumPy and scikit-learn Experience of taking models beyond the notebook and into production Understanding of MLOps, CI/CD and model deployment, or experience working closely with engineers A practical approach to modelling, with a preference for explainable solutions over unnecessary ...