Sr. Software Development Engineer, MLOPs
About The Position
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. Our team is building the foundational ML platform that powers autonomous robotics across Amazon’s fulfillment network. You’ll work at the intersection of large-scale distributed systems and cutting-edge ML research, turning novel vision-language-action models into production training workflows.
Requirements
- 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
Nice To Haves
- 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
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
Benefits
- sign-on payments
- restricted stock units (RSUs)
- health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
- 401(k) matching
- paid time off
- parental leave
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
Associate degree
