1 to 25 of 29 Amazon SageMaker Jobs in the UK

other related methods. MLOps & DevOps: MLflow, TFX, Kubeflow, Docker, Kubernetes, CI/CD terminology and pipelines in GIT, Jira Cloud & Infrastructure: AWS BedRock, SageMaker AI, Azure Machine Learning, GCP Vertex AI, Kubernetes, Terraform Data Engineering: Apache Kafka, Spark, Airflow, Parquet, SQL, NoSQL and graph databases. Optimization & Scheduling: Constraint optimization ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (e.g. Azure Cognitive Services, AWS SageMaker, and/or GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (e.g. Jenkins, Docker, Kubernetes, and/ ...

scalable lakehouse architectures (Delta Lake, Iceberg, Hudi) Cloud, Infrastructure & MLOps Champion multi-cloud engineering across Azure, AWS, and GCP Lead MLOps strategy (MLflow, Kubeflow, SageMaker, Vertex AI) and CI/CD pipelines Ensure scalable deployments using Kubernetes, Docker, and Infrastructure-as-Code Enterprise Integration (.NET Focus) Integrate AI capabilities ...

analytics workloads Cloud, Infrastructure & MLOps Champion multi-cloud engineering across Azure, AWS, and GCP within an enterprise-grade environment Lead MLOps strategy (MLflow, Kubeflow, SageMaker, Vertex AI) and industrialised CI/CD pipelines Ensure scalable, secure deployments using Kubernetes, Docker, and Infrastructure-as-Code Enterprise Integration (.NET Focus) Integrate ...

technical direction. End-to-End AI Delivery: Design, build, and maintain scalable AI and LLM-based pipelines using AWS or Azure services (e.g., SageMaker, Azure ML, Databricks, OpenAI integrations). Contribute across AI model lifecycles from data preprocessing and prompt engineering through to deployment and continuous monitoring in production ...

best practices Required Skills & Experience 1+ year hands-on experience deploying GenAI/LLM applications into production Experience with AWS services such as Lambda, SageMaker, Bedrock, S3, EC2 and ECS Strong Python development skills with modern AI/ML libraries Practical experience using at least one LLM API Solid ...

best practices Required Skills & Experience 1+ year hands-on experience deploying GenAI/LLM applications into production Experience with AWS services such as Lambda, SageMaker, Bedrock, S3, EC2 and ECS Strong Python development skills with modern AI/ML libraries Practical experience using at least one LLM API Solid ...

Weaviate, FAISS , Qudrant) Agentic AI frameworks (exposure to LangGraph, AutoGen, CrewAI or others) Exposure to cloud AI platforms (Azure AI Foundry, AWS Bedrock/SageMaker, GCP Vertex AI). Understanding of basic Responsible AI principles and safe deployment patterns. Ability to collaborate with cross-functional teams and contribute ...

NumPy, Pandas, SciPy, Scikit‐learn, TensorFlow, PyTorch, Transformers, Langchain, Streamlit, or Gradio, among others. Experience with cloud‐based tools for production use (e.g., AWS SageMaker, AWS Bedrock, Vertex AI, Azure Machine Learning, Azure OpenAI). Knowledge of databases and data technologies, such as Snowflake, BigQuery, and relational databases like ...

Python and ML/DL frameworks (e.g., scikit-learn, PyTorch, TensorFlow) Experience with AI/ML tools (e.g., Jupyter, MLflow, Vertex AI, Azure ML, Amazon SageMaker Experience of creating delivery client-facing proof of concepts Strong knowledge of cloud platforms (Azure, AWS, GCP) and MLOps best practices Experience ...

Python and SQL skills Understanding of data platforms (e.g. Snowflake/CDP) and ingestion pipelines Exposure to AI/ML enablement frameworks (.e.g AWS SageMaker) and supporting infrastructure for model training, deployment Familiarity with modern development and deployment frameworks Experience with dbt/ELT patterns (beneficial, not core focus ...

Generative AI models, LLMs, and agentic frameworks. •Collaborate with stakeholders to define problem statements and solution approaches. •Deploy models using MLOps tools such as SageMaker, Snowflake, and CI/CD pipelines. •Integrate vector databases and Retrieval-Augmented Generation (RAG) pipelines. •Ensure high-quality delivery and adherence to best practices ...

mathematical representation of complex systems (e.g., differential equation modelling and mathematical programming and optimisation). Experience with cloud computing (e.g. GCP, Azure ML, AWS SageMaker), containerisation (Docker, Kubernetes), or version control (Git). Disclosure and Barring Service Check This post is subject to the Rehabilitation of Offenders Act (Exceptions ...

Degree in a relevant technical field Tech Environment Python, Java Cloud platforms AWS Containerisation and infrastructure-as-code tools Relational and non-relational databases Amazon Bedrock, Sagemaker, Vertex AI Datadog, Databricks, MLFlow, Grafana, OTel Claude, Gemini, ChatGPT, open-weight LLM models Terraform, Docker, K8s RMDBs, Graph DBs, Vector ...

Python and SQL skills Understanding of data platforms (eg Snowflake/CDP) and ingestion pipelines Exposure to AI/ML enablement frameworks (.eg AWS SageMaker) and supporting infrastructure for model training, deployment Experience with dbt/ELT patterns (beneficial, not core focus) Strong stakeholder communication and technical leadership skills ...

systems (e.g. RAG, agentic workflows, NLP). Strong product and systems thinking with a practical, impact-led mindset. Nice to Have AWS experience (e.g. SageMaker, Bedrock, Lambda, S3, Redshift). Familiarity with MLOps practices. Background in adtech, media, fraud, or adversarial systems. Why Join Work on technically challenging, high ...

selection, and performance trade-offs Ability to assess use case viability and business value Cloud & Technology Experience across at least two of: AWS (Bedrock, SageMaker) Azure (Azure ML, Azure OpenAI) GCP (Vertex AI) OpenAI ecosystem Plus: Understanding of data engineering and big data concepts Awareness of cloud security, scalability ...

reliability of ML systems What We’re Looking For Proven experience with ML in production environments Strong skills in Python, SQL, and AWS (SageMaker, Lambda, etc.) Experience with NLPs or LLMs Familiarity with MLOps and real-time data applications A pragmatic mindset and strong problem-solving ability Background ...

ability to design scalable, cloud-native machine learning operations across traditional ML and modern LLM workflows. The ideal candidate will bring experience with SageMaker-based MLOps pipelines, evaluation of equivalent tooling stacks, hybrid MLOps/LLMOps automation, CI/CD orchestration, governance, monitoring, automation and production-grade scalability patterns. … deployment, versioning, monitoring, and CI/CD automation. Build container-oriented ML platforms (EKS-first) while evaluating alternative orchestration tools with similar capabilities (Kubeflow, SageMaker, MLflow, Airflow, etc.). Implement hybrid MLOps + LLMOps workflows, including prompt/version governance, evaluation frameworks, and monitoring for LLM-based systems. Serve ...

Tungsten Automation solutions Production AI Experience : Leverage experience with deploying, monitoring, and maintaining AI/LLM models in production (e.g., Azure ML, AWS Sagemaker, or Kubernetes-based ML pipelines) Thought Leadership : Provide thought leadership on AI-driven automation trends and best practices, both internally and externally Collaboration and Cross ...

rich metadata, automated quality profiling, and governance guardrails. Consumers: Reduce friction from discovery to access — self-service provisioning, entitlement workflows, one-click integration with SageMaker, Databricks, and EMR. Network effects: Analyze usage trends to improve data quality, discovery and relevancy across persona groups Collaborate with Engineering, Design & Data Science ...

environment evolves, but typical tools include: Python for experimentation, modelling, and evaluation Weights & Biases (or equivalent) for experiment tracking AWS , including services such as SageMaker and Bedrock Internally supported AI development platforms and tooling This role is not suited to candidates who are dogmatic about specific tools . Adaptability ...

environment evolves, but typical tools include: Python for experimentation, modelling, and evaluation Weights & Biases (or equivalent) for experiment tracking AWS, including services such as SageMaker and Bedrock Internally supported AI development platforms and tooling This role is not suited to candidates who are dogmatic about specific tools. Adaptability ...

solutions to effectively scale and maintain the data platform. You will tackle complex data challenges in a fast-paced, exciting environment, leveraging cutting-edge Amazon Web Services (AWS) technologies such as Lambda, SageMaker and Bedrock to develop innovative and scalable data solutions. After a suitable settling in period ...

solutions to effectively scale and maintain the data platform. You will tackle complex data challenges in a fast-paced, exciting environment, leveraging cutting-edge Amazon Web Services (AWS) technologies such as Lambda, SageMaker and Bedrock to develop innovative and scalable data solutions. After a suitable settling in period ...