Job Overview
Amazon Web Services (AWS) is seeking a Senior Software Engineer to join the Machine Learning Applications (ML Apps) team, focusing on AWS Neuron for distributed training. This role involves building, delivering, and maintaining complex products that impact millions globally, designing fault-tolerant systems that operate at massive scale in the AWS Cloud.
Responsibilities
- Lead the development of distributed training support in Pytorch and Tensorflow using XLA and the Neuron compiler and runtime stacks.
- Tune ML models to ensure high performance and efficiency on AWS Trainium and Inferentia silicon and TRn1, Inf1 servers.
- Collaborate with chip architects, compiler engineers, and runtime engineers to build and optimize distributed training solutions.
Qualifications
Basic Qualifications
- 3+ years of non-internship professional software development experience.
- Experience in design or architecture of new and existing systems.
- Proficiency in programming with at least one software programming language.
- Deep learning industry experience.
Preferred Qualifications
- Experience with full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations.
- Bachelor's degree in computer science or equivalent.
- Expertise in Pytorch, Jax, Tensorflow, distributed libraries, and frameworks.
- Experience in end-to-end model training.
About the Team
The ML Apps team at AWS Neuron works closely with various disciplines including silicon engineering, hardware design and verification, software, and operations. The team is dedicated to supporting new members, promoting knowledge sharing and mentorship, and is committed to providing a work environment that balances professional challenges with personal life.
Benefits
- Flexible working hours to support work-life balance.
- Opportunities for mentorship and career growth within the company.
- Inclusive team culture with a focus on employee well-being.
Benefits Extracted with AI
- Flexible working hours
- Work-life balance support
- Mentorship and career growth opportunities
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