About the job
We are looking for a Senior Software Development Engineer with deep expertise in machine learning operations to join the Data & Intelligence Foundation (DIF) team within Amazon. You will design, build, and operate the ML training infrastructure that enables robot learning at scale — from distributed GPU training pipelines to experiment tracking, data management, and model deployment.
Responsibilities
- Design and implement scalable ML training infrastructure on Kubernetes (EKS) with GPU scheduling and fault-tolerant distributed training
- Build and maintain CI/CD pipelines for ML models — from data ingestion through training, evaluation, and deployment
- Develop tooling for experiment tracking, hyperparameter optimization, and reproducibility
- Architect data pipelines that handle large-scale robotics datasets (telemetry, sensor recordings, demonstrations)
- Collaborate with research scientists to operationalize novel ML models into production
- Establish monitoring, alerting, and observability for training workloads and model performance
- Drive best practices for GPU fleet management, cost optimization, and capacity planning
Qualifications
Minimum
- 5+ years of non-internship professional software development experience
- 5+ years of programming with at least one software programming language experience
- 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- Experience as a mentor, tech lead or leading an engineering team
Preferred
- 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Bachelor's degree in computer science or equivalent
- Knowledge of Machine Learning and LLM fundamentals, including transformer architecture, training/inference lifecycles, and optimization techniques
- Knowledge of ML frameworks including JAX, PyTorch, vLLM, SGLang, Dynamo, TorchXLA, and TensorRT