1 to 25 of 51 Amazon SageMaker Jobs in the UK

ecosystems Visualisation & APIs: REST/JSON, Postman, Flask/FastAPI, Power BI/Tableau, D3.js DevOps & Cloud: CI/CD, Docker, AWS (S3, Lambda, SageMaker), Kubernetes, Terraform/CDK ML Ops & Automation: MLFlow, feature stores, model monitoring, A/B testing Data Security & Compliance: Secure SDLC, ISO/NIST ...

creating pipelines that integrate seamlessly into production environments. Extensive experience in cloud environments (AWS, Azure, or GCP), including leveraging cloud-native AI tools like SageMaker, Vertex AI, or Azure ML Studio. Demonstrable expertise in creating interactive dashboards and visual analytics using tools such as Tableau, Plotly, Dash, or D3.js. ...

need: Strong Python and experience with TensorFlow, PyTorch or scikit-learn Hands-on LLM work—prompt engineering, modern NLP techniques AWS experience: SageMaker, Bedrock, S3, Lambda, CloudWatch Understanding of deep learning, transformers and attention mechanisms Knowledge of RAG systems, vector databases and embeddings Experience deploying ML models to production ...

preferred Hands-on experience with GCP Vertex AI model endpoints, pipelines, embeddings, vector search or equivalent cloud-native AI/ML platforms e.g. AWS SageMaker, Azure ML and agent orchestration frameworks e.g. LangChain, LangGraph Solid understanding of MLOps CI/CD, IaC Terraform, experiment tracking, model registry, and monitoring ...

least one major cloud provider. AWS, GCP or Azure Familiar with Docker and CI/CD pipelines Experience with managed ML platforms such as SageMaker, Vertex AI or Azure ML Data engineering and MLOps Experience with data warehouses such as Snowflake, BigQuery or Redshift Workflow orchestration using tools like ...

experience with ML frameworks (PyTorch, TensorFlow, Scikit-learn). Is experienced with cloud platforms (ideally GCP: BigQuery, Vertex AI, Dataflow), but AWS/SageMaker or similar is also valued. Has operated in distributed computing environments, working with large datasets and parallelized processing. Can communicate technical concepts and trade-offs ...

experience with ML frameworks (PyTorch, TensorFlow, Scikit-learn). Is experienced with cloud platforms (ideally GCP: BigQuery, Vertex AI, Dataflow), but AWS/SageMaker or similar is also valued. Has operated in distributed computing environments, working with large datasets and parallelized processing. Can communicate technical concepts and trade-offs ...

vector databases (Pinecone, Weaviate, OpenSearch), or multi-agent orchestration. Experience building conversational agents or AI-driven automation systems. Knowledge of MLOps tooling such as SageMaker, MLflow, or Databricks. Familiarity with RLHF, alignment techniques, or model interpret ability. Interest in consumer behaviour, research methodologies, or product decision-making. Startup experience ...

vector databases (Pinecone, Weaviate, OpenSearch), or multi-agent orchestration. Experience building conversational agents or AI-driven automation systems. Knowledge of MLOps tooling such as SageMaker, MLflow, or Databricks. Familiarity with RLHF, alignment techniques, or model interpret ability. Interest in consumer behaviour, research methodologies, or product decision-making. Startup experience ...

effort and costs Nice to have * CI/CD experience (Azure DevOps, GitHub Actions, Jenkins)* Exposure to ML Ops tooling (Azure ML, AI Foundry, SageMaker or Vertex AI)* Infrastructure-as-Code (Bicep, ARM, Terraform)* Previous work building Gen AI-powered products or automation Tech environment you'll be joining ...

capability to guide engineering teams and influence technical strategy. Some other highly valued skills may include: Experience with MLOps platforms such as Databricks or SageMaker, and familiarity with hybrid cloud strategies (Azure, on-prem Kubernetes). Strong understanding of AI infrastructure for scalable model serving, distributed training ...

capability to guide engineering teams and influence technical strategy. Some other highly valued skills may include: Experience with MLOps platforms such as Databricks or SageMaker, and familiarity with hybrid cloud strategies (Azure, on-prem Kubernetes). Strong understanding of AI infrastructure for scalable model serving, distributed training ...

technologies Preferred Qualifications, Capabilities, And Skills Background in STEM with exposure to machine learning systems Experience with MLOps tools and platforms (e.g., MLflow, Amazon SageMaker, Databricks, BentoML, Arize) Hands-on experience with cloud computing platforms like AWS, Azure, or GCP Experience working in highly regulated environments or industries ...

production environments. Strong Python skills, with experience in frameworks like PyTorch, TensorFlow, or Hugging Face. Confident working in AWS or similar cloud environments (SageMaker, Lambda, Docker, etc.). Experienced in (or eager to explore) areas such as forecasting, optimisation, reinforcement learning, generative AI, or computer vision. Solid engineering mindset ...

production environments. Strong Python skills, with experience in frameworks like PyTorch, TensorFlow, or Hugging Face. Confident working in AWS or similar cloud environments (SageMaker, Lambda, Docker, etc.). Experienced in (or eager to explore) areas such as forecasting, optimisation, reinforcement learning, generative AI, or computer vision. Solid engineering mindset ...

Hands-on ownership of CI/CD (Jenkins/Azure DevOps/GitHub Actions) and MLOps in Azure ML/Azure AI Foundry/SageMaker/Vertex AI. Working knowledge of Infrastructure as Code (Bicep, ARM, Terraform). A test-driven development mindset and commitment to engineering quality. Broad ...

Technical Knowledge: Strong understanding of modern AI/ML technologies and cloud-based solutions. Tools & Platforms: Familiarity with Snowflake, Databricks, Azure AI Foundry , AWS SageMaker, and other leading platforms. Data Science Expertise: Knowledge of data science fundamentals, solution lifecycles, and MLOps methodology. Generative AI Knowledge: Experience with LLMs, neural ...

production using Python and modern ML frameworks. Hands-on experience with tools such as: scikit-learn, PyTorch, or TensorFlow for model development. AWS Bedrock, Sagemaker, HuggingFace, or equivalent cloud AI stacks. CrewAI or other orchestration frameworks for agentic AI systems. Pandas, NumPy, Airflow, or Databricks for data engineering ...

Python, SQL, and core ML libraries (e.g., Pandas, NumPy, Scikit-Learn, XGBoost). Strong experience working with cloud-based ML platforms (AWS preferred, e.g., SageMaker). Familiarity with model management and deployment tooling such as Git, MLflow, or CI/CD frameworks. Ways of Working. Clear and concise communicator ...

have a background in C#) Knowledge of AI principles and AI ethics Knowledge of data safety in LLM usage Experience with: AWS: boto3, Bedrock, SageMaker, Lambda, S3, EC2 Azure: Azure OpenAI Service, Cosmos DB Retrieval-Augmented Generation (RAG), Graph RAG Embedding models and LLM training fundamentals Damia Group Limited ...

visualisation languages and libraries (SQL, python and/or R, matplotlib/ggplot etc.) as well as supporting tools and platforms (e.g. git, Sagemaker, VS Code) A strong understanding of statistical concepts (hypothesis testing, sampling, probability distributions). Excellent communication and collaboration skills to effectively bridge the gap between ...

/SQL); CI/CD & IaC (GitHub/GitLab, CloudFormation); observability (CloudWatch + data quality/lineage tooling); ThoughtSpot as the visualisation layer; MLOps (SageMaker and/or MLflow Model Registry). Why join us? We’re on a journey to become market leaders in our space – and with ...

/ML concepts: supervised and unsupervised learning, GenAI, LLMs, embeddings, MLOps, vector search. Experience designing AI solutions using tools such as Azure ML, AWS SageMaker, Google Vertex AI, Databricks, LangChain, and Hugging Face. Ability to develop architecture artefacts (e.g., HLDs), technical narratives, effort estimates, and proposal content. Exceptional storytelling ...

/ML concepts: supervised and unsupervised learning, GenAI, LLMs, embeddings, MLOps, vector search. Experience designing AI solutions using tools such as Azure ML, AWS SageMaker, Google Vertex AI, Databricks, LangChain, and Hugging Face. Ability to develop architecture artefacts (e.g., HLDs), technical narratives, effort estimates, and proposal content. Exceptional storytelling ...

implementation. Required Skills & Experience Deep experience architecting and scaling enterprise-grade AI/ML systems . Proven expertise with cloud AI ecosystems (AWS Bedrock, SageMaker, Azure OpenAI, Azure ML). Strong command of agent frameworks , vector databases , and LLM orchestration tools . Ability to lead multi-disciplinary teams ...