18 of 18 Amazon SageMaker Jobs in the UK

with cloud-native development GCP 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. ·Proven experience deploying and operating More ❯

with Single Sign-On/OIDC integration and a deep understanding of OAuth, JWT/JWE/JWS. Solid understanding of backend performance optimization and debugging. Knowledge of AWS SageMaker and data analytics tools. Proficiency in frameworks TensorFlow, PyTorch, or similar. Preferred Qualifications, Capabilities, and Skills: Familiarity with LangChain, Langgraph, or any Agentic Frameworks is a strong plus. Python More ❯

geospatial libraries such as GeoPandas, Shapely, and GDAL Advanced knowledge of PostgreSQL/PostGIS for spatial data management Experience with AWS and Azure platforms, including AI services (e.g., AWS SageMaker, Azure ML) Proven experience developing or deploying AI models across domains such as natural language processing, computer vision, or predictive analytics Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch More ❯

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

of stakeholders* Confidence estimating development 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 Python, C#Azure Data Factory, Logic More ❯

using SQL and NoSQL databases. 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 understanding of ML approaches, with More ❯

model development, validation, deployment, monitoring, and maintenance Awesome If You: Have experience in the energy sector or understanding of energy systems and operations Have practical experience with AWS services (SageMaker, S3, EC2, Lambda, etc.) Have experience with infrastructure as code tools (Terraform, CloudFormation) Have experience with Apache Kafka and real-time streaming frameworks Are familiar with observability principles such More ❯

required to contribute: Years of overall Data and Analytics experience with 2. Minimum 10+ years in AWS data platform including AWS S3, AWS Glue, AWS Redshift, AWS Athena, AWS Sagemaker, AWS Quicksight and AWS MLOPS 3. Snowflake DWH architecture, Snowflake Data Sharing, Snowpipe, Polaris catalog and data governance (meta data/business catalogs). 4. Knowledge of at least More ❯

version control, CI/CD, and collaboration. • Strong coding background in Python and PySpark. • Hands-on experience with the following AWS services: o S3, Lambda, Glue, Step Functions, Athena, SageMaker, VPC, ECS, IAM, KMS • Proficiency in CloudFormation for infrastructure automation. • Experience with unit testing frameworks and best practices. • Familiarity with GitLab for source control and CI/CD ABOUT More ❯

.NET/C# (Key to 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 acts as an employment agency More ❯

and SLMs — with an understanding of performance, suitability, training needs, and deployment approaches. Practical hands-on experience with at least two hyperscaler AI platforms , such as: AWS Bedrock/SageMaker Google Vertex AI OpenAI Azure ML Solid understanding of statistics, machine learning, data science fundamentals, data engineering, and big data concepts. Knowledge of the process, data prerequisites, and success More ❯

simplify complex systems for enterprise users. Experience in early-stage or high-growth environments. Preferred Experience Experience building or managing AI and data platform products such as Vertex AI, SageMaker, or Azure ML. Familiarity with agent-based automation, orchestration stacks, and MLOps platforms. Knowledge of modern enterprise data platforms and how they integrate with AI and ML workflows. Background More ❯

Claude, Gemini, Mistral, LLaMA, Cohere). Experiment with advanced prompting techniques; Chain-of-Thought, ReAct, Tree-of-Thoughts, and more. Deploy AI/ML pipelines using Azure ML, AWS SageMaker, Vertex AI, or Databricks. Integrate LLMs into production apps using LangChain, LlamaIndex, and RAG architectures. Build APIs and microservices for scalable AI deployment. Use AI-powered dev tools like … related field. Tech Stack LLMs: GPT-4/5, Claude, Gemini, Mistral, LLaMA, Cohere Frameworks: LangChain, LlamaIndex, Haystack Tools: GitHub Copilot, Cursor, PromptLayer, Weights & Biases Cloud: Azure ML, AWS SageMaker, Google Vertex AI, Databricks Infra: Python, Docker, Kubernetes, SQL, PyTorch More ❯

from architecture to production—and help shape best practices in security, automation, and cost-efficient AI deployment. Key Responsibilities Architect secure, scalable ML and GenAI systems using AWS services (SageMaker, EKS/Fargate, Lambda, Step Functions). Build CI/CD pipelines for ML models, agents, and GenAI applications. Deploy LLMs and orchestrate multi-agent systems (LangChain, LangGraph, or … across all ML workflows. Mentor junior engineers and promote engineering best practices. Key Requirements Essential 3+ years experience in MLOps/ML Engineering/AIOps. Strong expertise in AWS (SageMaker, EKS/Fargate, Lambda, Step Functions, S3). Proficient with Docker, Kubernetes , and IaC (Terraform or AWS CDK). Experience with MLflow , CI/CD tools, and automated testing. More ❯

search, reranking, embedding optimization, chunking strategies and evaluation harnesses. Develop APIs, microservices and serverless workflows for scalable deployment. ML/LLM Engineering Work with AI+ML pipelines throughAzure ML,AWS SageMaker,Vertex AI,Databricks, orModal/Fly.iofor lightweight LLM deployment. Utilizevector databases(Pinecone, Weaviate, Milvus, ChromaDB, pgVector) and embedding stores. UseAI-powered dev tools(GitHub Copilot, Cursor, Codeium, Aider, Windsurf … 2.x, Mistral Large, LLaMA 3, Cohere Command R+, DeepSeek Frameworks: LangChain, LlamaIndex, Haystack, AutoGen, CrewAI Tools: GitHub Copilot, Cursor, LangSmith, LangFuse, Weights & Biases, MLflow, Humanloop Cloud: Azure ML, AWS SageMaker, Google Vertex AI, Databricks, Modal Infra: Python, Docker, Kubernetes, SQL/NoSQL, PyTorch, FastAPI, Redis More ❯

Data ScientistHybrid Working - Local Site - 1-2 days a week on site.Financial ServicesLorien's leading banking client is looking for a number of Data Scientists to join them on a new long term project which will be working on GenAI More ❯

bid responses. Implement Governance and Security: Define and enforce data governance, security, and compliance strategies. Hands-On Expertise: Work with AWS services such as Redshift, Glue, Lake Formation, Athena, SageMaker, and more. Mentor and Build Capability: Support the growth of junior team members and contribute to internal capability development. What We're Looking For AWS Expertise: Proven experience designing … and implementing data platforms using AWS services (Redshift, Glue, Lake Formation, SageMaker, Athena). Data Architecture Skills: Strong background in data lakes, lakehouses, data warehouses, and real-time analytics solutions. Cloud Modernisation Experience: Experience migrating on-premises systems to cloud-native architectures. Automation & DevOps: Familiarity with CI/CD and AWS DevOps practices. Containerisation & Orchestration: Knowledge of Docker, Kubernetes More ❯

their consulting delivery team, supporting key financial services and banking clients. The assignment focuses on designing and building an advanced model developer environment for containerised model deployments on AWS SageMaker , with GenAI/agentic capabilities embedded into the platform. You will also lead a team of four developers and collaborate closely with data engineering, data science and platform teams. … Experience Banking experience is essential Strong software engineering background with expert Python Hands-on experience with GitLab CI/CD Extensive Docker containerisation & runtime experience Strong understanding of AWS SageMaker deployments Experience building developer environments for ML/quant/data-intensive workflows Knowledge of monitoring, logging, reporting and test automation Proven team leadership of small development teams Strong More ❯