Job ID: 2793426 | Amazon Development Center U.S., Inc.
AWS AI is looking for world-class software developers to join the Deep Learning cross-framework team. In this organization, you will be responsible for developing communications collectives like AllGather and Reduce Scatter. You will also develop cross-framework solutions to support training of Deep Learning models at scale, involving thousands of accelerators. You will be working in a fast-paced, cross-disciplinary team of engineers and researchers who are leaders in the field. You will take on challenging problems, elicit requirements, and deliver innovative solutions into production that consolidate the AI team as thought leaders in the space.
Inclusive Team Culture
Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences.
Work/Life Balance
Our team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.
Mentorship & Career Growth
Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer.
Key Job Responsibilities
As a Software Development Engineer in the SageMaker Engines team, you will be responsible for:
- Developing innovative solutions for supporting Large Language Model training in a cluster of nodes;
- Implementing model parallelism methods such as pipeline and tensor parallelism as extensions to the PyTorch framework;
- Implementing sharding of the model training state, activation checkpointing/offloading and other memory saving techniques;
- Optimizing distributed training by profiling, identifying bottlenecks and addressing them by improving compute and network performance, as well as finding opportunities for better compute/communication overlap;
- Optimizing communication collectives for the AWS network infrastructure.
A Day in the Life
The SageMaker Engines team develops technology for supporting training of Deep Learning models at large scale. This entails implementation of model parallelism and memory saving techniques to allow training of models across accelerators as well as implementation of network communication collectives optimized for the AWS infrastructure.
About the Team
AWS values diverse experiences. Even if you do not meet all of the preferred 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.
Why AWS?
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
BASIC QUALIFICATIONS
- 3+ years of non-internship professional software development experience;
- 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience;
- Experience programming with at least one software programming language.
PREFERRED QUALIFICATIONS
- 3+ 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;
- Experience building complex software systems that have been successfully delivered to customers;
- Experience with CUDA development.
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.
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