Sr. Software Engineer- AI/ML, AWS Neuron Apps

- 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
- Bachelor's degree in computer science or equivalent

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. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $151,300/year in our lowest geographic market up to $261,500/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.
AWS Neuron is the complete software stack for the AWS Inferentia and Trainium cloud-scale machine
learning accelerators and the Trn1 and Inf1 servers that use them. This role is for a senior software engineer in the Machine Learning Applications (ML Apps) team for AWS Neuron. This role is responsible for development, enablement and performance tuning of a wide variety of ML model families, including massive scale large language models like GPT2, GPT3 and beyond, as well as stable diffusion, Vision Transformers and many more.

The ML Apps team works side by side with chip architects, compiler engineers and runtime engineers to create , build and tune distributed training solutions with Trn1. Experience training these large models using Python is a must. FSDP, Deepspeed and other distributed training libraries are central to this and extending all of this for the Neuron based system is key.

*Utility Computing (UC)*
AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services.

Key job responsibilities
This role will help lead the efforts building distributed training and inference support into Pytorch, Tensorflow using XLA and the Neuron compiler and runtime stacks. This role will help tune these models to ensure highest performance and maximize the efficiency of them running on the customer AWS Trainium and Inferentia silicon and the TRn1 , Inf1 servers. Strong software development and ML knowledge are both critical to this role.

About the team
**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.

**Diverse Experiences**
Amazon 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.

**Work/Life Balance* *
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

**Inclusive Team Culture* *
Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.

**Mentorship and 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.