As a Software Development Engineer, you will design and build systems that combine machine learning, real-time data processing, simulation, and large language models (LLMs). Your work will directly influence how Amazon’s robotic systems operate—driving measurable improvements in throughput, safety, and efficiency across global fulfillment networks.

Design and build agentic AI systems that combine machine learning models, real-time data, and LLM-driven reasoning to automate operational decision-making in robotic workflows.

Develop end-to-end decision systems that observe system state, generate insights, and trigger safe, validated actions through robust safeguards and control mechanisms.

Build scalable, event-driven architectures on AWS to support real-time and batch processing for inference, decisioning, and continuous feedback loops.

Design and implement machine learning models for perception, classification, prediction, and optimization, and integrate them into production systems.

Develop and manage data pipelines, model training workflows, and deployment infrastructure, ensuring reliable and scalable ML Ops practices.

Collaborate with simulation teams to test and validate decision strategies in virtual environments prior to production rollout.

Conduct offline and in-simulation experimentation and analysis to continuously improve model performance and system outcomes.

Partner with cross-functional teams including data scientists, data engineers, simulation developers, and operations leaders to deliver end-to-end solutions.

Implement observability, monitoring, and evaluation frameworks to ensure reliability, safety, and performance of automated systems.

Own production systems end-to-end, including deployment, monitoring, retraining, and continuous improvement.

Contribute to the technical architecture and roadmap for agentic AI and ML-driven robotics platforms within AR Sortation Insights.