Amazon Sr Software Engineer- AI/ML AWS Neuron Distributed Training 

United States, California, Cupertino 

729980509

Key job responsibilities
You will help lead the efforts building distributed training support into Pytorch, Tensorflow using XLA and the Neuron compiler and runtime stacks. You will help tune these models to ensure highest performance and maximize the efficiency of them running on the custom AWS Trainium and Inferentia silicon and the Trn1, Inf1/2 servers. Strong software development and Machine Learning knowledge are both critical to this role.Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.About AWSWork/Life Balance
Mentorship & Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

- Bachelor's degree in computer science or equivalent
- 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
- 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Experience as a mentor, tech lead or leading an engineering team
- Experience in machine learning, data mining, information retrieval, statistics or natural language processing

- Master's degree in computer science or equivalent
- Experience in computer architecture
- Previous software engineering expertise with Pytorch/Jax/Tensorflow, Distributed libraries and Frameworks, End-to-end Model Training.