AI/ML Engineer Sr.

Design and operate reproducible data pipelines for training and inference, ensuring consistency between training and serving. Deploy, version, and monitor machine learning models on Amazon SageMaker, managing rollback strategies, drift detection, and latency. Build end-to-end agent workflows using modern orchestration frameworks to handle state, tools, and fault tolerance. Integrate language models on Amazon Bedrock, optimizing prompts, throughput, and costs while integrating with external APIs. Develop high-performance distributed Python services with Temporal, focusing on concurrency, backpressure, and profiling. Define evaluation frameworks for observability, tracking traces, metrics, and hallucination rates. Ensure all solutions adhere to security, privacy, and data governance standards. Collaborate on CI/CD pipelines and infrastructure as code.