5 of 5 Permanent Amazon SageMaker Jobs in the Midlands

data analysts, engineers, and architects to improve model performance and integrate insights. The successful candidate will: Have proficiency with AWS cloud services such as SageMaker, Lambda, S3, Step Functions, EMR, and Glue. Understand the machine learning development cycle, including data engineering, analysis, modeling, and operations. Design and implement scalable More ❯

Serve models using vLLM, DeepSpeed, Triton, TensorRT Multi-Agent Orchestration: Work with LangChain, AutoGen, CrewAI, DSPy and similar tools Cloud & MLOps (AWS): Deploy with SageMaker, Bedrock, Lambda, S3, ECS, EKS Full-Stack Integration: Build APIs (FastAPI, Flask) and integrate with React, TypeScript, Node.js Vector Search: Use FAISS, Weaviate, Pinecone More ❯

agentic capabilities using frameworks such as LangChain, CrewAI, AutoGen, and DSPy. AWS Cloud & MLOps: Deploy scalable machine learning workloads on AWS using services like SageMaker, Bedrock, Lambda, S3, DynamoDB, ECS, and EKS. End-to-End AI Product Development : Work across the full ML lifecycle, from data collection and preprocessing More ❯

agentic capabilities using frameworks such as LangChain, CrewAI, AutoGen, and DSPy. AWS Cloud & MLOps: Deploy scalable machine learning workloads on AWS using services like SageMaker, Bedrock, Lambda, S3, DynamoDB, ECS, and EKS. End-to-End AI Product Development : Work across the full ML lifecycle, from data collection and preprocessing More ❯

and experience of Data Governance frameworks and implementation. Exposure to CI/CD pipelines and source control for reports and analytics. Bonus: Familiarity with SageMaker or similar ML/predictive analytics platforms. We're looking for someone who: Thinks like a data user, not just a data builder with More ❯