1 to 25 of 35 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 ...

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 ...

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 ...

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 ...

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 ...

/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 ...

LLMs (Large Language Models), generative models, and related frameworks (e.g., LangChain, TensorFlow, etc.) Possess knowledge of cloud-based AI/ML services like AWS SageMaker, Azure Machine Learning, Google AI Platform, Databricks GenAI/BI, Snowflake GenAI, and their relevant services for building and deploying GenAI workloads. Knowledge ...

software solutions. • Expertise in AI Model Architecture – LLMs, SLMs, performance, training, deployment. • Hands-on experience with at least two hyperscaler platforms: AWS Bedrock/SageMaker, Google Vertex AI, Azure ML, OpenAI. • Strong understanding of statistics, machine learning, data science, and big data. • Knowledge of cloud security, landing zones ...

expertise in one or more of the following: NoSQL databases (e.g., DocumentDB, MongoDB) RDF/graph technologies (e.g., GraphDB) AI/ML platforms (e.g., SageMaker, Bedrock) Search technologies (e.g., Solr, OpenSearch, Elasticsearch) Cloud-based data pipeline engineering (AWS) Produce clean, testable, maintainable code that supports incremental innovation. Build ...

expertise in one or more of the following: NoSQL databases (e.g., DocumentDB, MongoDB) RDF/graph technologies (e.g., GraphDB) AI/ML platforms (e.g., SageMaker, Bedrock) Search technologies (e.g., Solr, OpenSearch, Elasticsearch) Cloud-based data pipeline engineering (AWS) Produce clean, testable, maintainable code that supports incremental innovation. Build ...

scale data analytics (e.g. Spark/PySpark) Experience in writing, testing and implementing scripts (e.g. Python, Scala) Experience of cloud data stack use (e.g. SageMaker Notebooks, S3, Glue, Athena) Communicating technical concepts clearly to both technical and non-technical stakeholders using appropriate language and methods. Profiling data and analysing ...

scale data analytics (e.g. Spark/PySpark) Experience in writing, testing and implementing scripts (e.g. Python, Scala) Experience of cloud data stack use (e.g. SageMaker Notebooks, S3, Glue, Athena) Communicating technical concepts clearly to both technical and non-technical stakeholders using appropriate language and methods. Profiling data and analysing ...

scale data analytics (e.g. Spark/PySpark) Experience in writing, testing and implementing scripts (e.g. Python, Scala) Experience of cloud data stack use (e.g. SageMaker Notebooks, S3, Glue, Athena) Communicating technical concepts clearly to both technical and non-technical stakeholders using appropriate language and methods. Profiling data and analysing ...

large-scale analytics engines (e.g. Spark/PySpark) and scripting languages such as Python or Scala. Hands-on use of cloud data stacks (e.g. SageMaker Notebooks, S3, Glue, Athena) and modern storage formats or frameworks (e.g. Parquet, Delta Lake, Fabric). Experience with DevOps/DataOps tooling and practices ...

large-scale analytics engines (e.g. Spark/PySpark) and scripting languages such as Python or Scala. Hands-on use of cloud data stacks (e.g. SageMaker Notebooks, S3, Glue, Athena) and modern storage formats or frameworks (e.g. Parquet, Delta Lake, Fabric). Experience with DevOps/DataOps tooling and practices ...