Description

The Product: AWS Machine Learning accelerators are at the forefront of AWS innovation. The Inferentia chip delivers best-in-class ML inference performance at the lowest cost in cloud. Trainium delivers the best-in-class ML training performance with the most teraflops (TFLOPS) of compute power for ML in the cloud. This is all enabled by cutting edge software stack, the AWS Neuron Software Development Kit (SDK), which includes ML compiler, runtime and natively integrates into popular ML frameworks, such as PyTorch, TensorFlow and JAX. AWS Neuron along with the Inferentia/Trainium chips are used at scale with customers and partners both internal and external to Amazon.

The Team: The Amazon Annapurna Labs team is a responsible for building innovation in silicon and software for AWS customers. We are at the forefront of innovation by combining cloud scale with the world’s most talented engineers. Our team covers multiple disciplines including silicon engineering, hardware design and verification, software and operations. With such breadth of talent, there's opportunity to learn all of the time. We operate in spaces that are very large, yet our teams remain small and agile. There is no blueprint. We're inventing. We're experimenting. When you couple that with the ability to work on so many different products and services, it's a very unique learning culture.

Key job responsibilities

You: We are seeking a talented SW Engineering Manager with strong leadership/ mentoring skills to join our Deep Learning Compiler Team. As a Manager III you be building and leading a team of talented compiler engineers developing graph level optimizations to map SOTA deep learning models efficiently to our accelerator capabilities. You’ll leverage your technical skills to collaborate with ML applications teams and applied scientists developing the models to accelerate research ideas and techniques to bring them to production to faster serve our customers to their performance goals. You will partner with Pytorch, OpenXLA and other open source communities to leverage the work in both directions for the benefit of the machine learning community.

We are open to hiring candidates to work out of one of the following locations:

Cupertino, CA, USA

Basic Qualifications

• 3+ years of engineering team management experience

• 7+ years of working directly within engineering teams experience

• 3+ years of designing or architecting (design patterns, reliability and scaling) of new and existing systems experience

• Experience partnering with product or program management teams

Preferred Qualifications

• Experience in communicating with users, other technical teams, and senior leadership to collect requirements, describe software product features, technical designs, and product strategy

• Experience in recruiting, hiring, mentoring/coaching and managing teams of Software Engineers to improve their skills, and make them more effective, product software engineers

• M.S. or Ph.D. in Computer Science or related technical field

• Experience with XLA, TVM, MLIR, LLVM, deep learning models and algorithms, and deep learning framework design.

• Interactions with open-source communities, in either a leadership or code contributor role

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 $148,000/year in our lowest geographic market up to $287,700/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.