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 will deliver 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 an ML compiler, runtime and natively integrates into popular ML frameworks, such as PyTorch, TensorFlow and MxNet. The Neuron SDK optimizes performance of complex neural net models executed on AWS Inferentia. AWS Neuron and Inferentia are used at scale with customers and partners like PyTorch, Epic Games, Snap, AirBnB, Autodesk, Amazon Alexa, Amazon Rekognition and more customers in various other segments.
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.
Learn more about Our History:
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 leading a team of experienced compiler engineers developing compiler optimization algorithms and deploying, at scale, a new compiler targeting AWS custom hardware. You'll need to be technically capable, credible, and curious in your own right as a trusted AWS Neuron Manager, innovating on behalf of our customers. You’ll leverage your technical communications skill as a hands-on partner to AWS ML services teams, involved in pre-silicon design, bringing new products/features to market. As deep learning models become more versatile, using compiler technologies to achieve both high performance and high productivity becomes essential. Join the team to build the software that will boost the entire deep learning community.
You will have deep knowledge of resource management, scheduling, code generation, optimization, and new instruction architectures including CPU, NPU, GPU and novel forms of compute.
Explore the Product:
In order to be considered for this role, candidates must be currently located or willing to relocate to Cupertino (preferred), Seattle, or Austin.
About the team
Inclusive Team Culture
Here at Annapurna Labs, 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. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.
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. Our senior members enjoy one-on-one mentoring. 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 and enable them to take on more complex tasks in the future.
We are open to hiring candidates to work out of one of the following locations:
Austin, TX, USA | Cupertino, CA, USA | Seattle, WA, USA
- 5+ years of engineering team management experience
- 9+ years of working directly within engineering teams experience
- 4+ years of designing or architecting (design patterns, reliability and scaling) of new and existing systems experience
- Experience partnering with product or program management teams
- Deep understanding of compilers (resource management, instruction scheduling, code generation, and compute graph optimization)
- Strong software design fundamentals and excellent system-level coding skills with an emphasis on graph theory and performance techniques
- M.S. or Ph.D. in Computer Science or related technical field
- Experience with toolchains (LLVM, GCC) and code generation techniques for new hardware
- 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. Applicants should apply via our internal or external career site.