The Product: AWS Machine Learning accelerators are at the forefront of AWS innovation. Trainium delivers best-in-class ML training performance with the most teraflops (TFLOPS) of compute power for ML in the cloud. This is all enabled by the AWS Neuron Software Development Kit (SDK), which includes an ML compiler, the Neuron Kernel Interface (NKI) compiler, and a runtime that natively integrates into popular ML frameworks such as PyTorch and JAX.
Neuron Kernel Interface (NKI) is a bare-metal language and compiler for directly programming NeuronDevices available on AWS Trainium instances. You can use NKI to develop, optimize, and run new operators directly on NeuronCores while making full use of available compute and memory resources.
Explore NKI:
https://awsdocs-neuron.readthedocs-hosted.com/en/latest/nki/index.html
AWS Neuron is used at scale by customers such as Epic Games, Snap, Airbnb, Autodesk, Amazon Alexa, and Amazon Rekognition, along with many others across a range of segments.
The Team: The Amazon Annapurna Labs team is responsible for building innovative silicon and software for AWS customers. We are at the forefront of innovation, 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 is 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 makes for a unique learning culture.
Learn more about our history: https://www.amazon.science/how-silicon-innovation-became-the-secret-sauce-behind-awss-success
You: As a Sr. Machine Learning Compiler Engineer on the NKI team, you will be a thought leader supporting the ground-up development and scaling of a compiler that handles the world's largest ML workloads. Architecting and implementing business-critical features, publishing cutting-edge work, and mentoring a team of experienced engineers is what excites and challenges you. You will leverage your technical communication skills as a hands-on partner to AWS ML teams. A background in machine learning and AI accelerators is preferred, but not required.
In order to be considered for this role, candidates must be currently located in or willing to relocate to Seattle, Cupertino, or Austin.
About the team
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. Amazon’s culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.
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 professional and enable them to take on more complex tasks in the future.
