Deep Learning Compiler Engineer II, AWS Neuron, Annapurna Labs

DESCRIPTION

At AWS our vision is to make deep learning pervasive for everyday developers and to democratize access to cutting edge infrastructure.

In order to deliver on that vision, we've created innovative software and hardware solutions that make it possible.

AWS Neuron is the SDK that optimizes the performance of complex neural net models executed on AWS Inferentia and Trainium, our custom chips designed to accelerate deep-learning workloads

The Neuron SDK consists of a compiler, run-time, and debugger, integrated with Tensorflow, PyTorch, and MXNet. It's preinstalled in AWS Deep Learning AMIs and Deep Learning Containers for customers to quickly get started with running high performance and cost-effective inference.

The Neuron team is hiring senior compiler engineers in order to solve our customers toughest problems.

This is an opportunity to work on cutting-edge products at the intersection of machine-learning, high-performance computing, and distributed architectures.

You will architect and implement business-critical features, publish cutting-edge research, and mentor a brilliant team of experienced engineers.

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.

It is a very unique learning culture.

As a senior deep learning compiler engineer on the Neuron team, you will be a thought leader supporting the development of a compiler targeting AWS Inferentia and Trainum.

You will be developing and scaling the compiler to handle the world's largest ML workloads. You will need to be technically capable, credible and curious in your own right as a trusted AWS Neuron engineer, innovating on behalf of our customers.

You will leverage your technical communications skill as a hands-on partner to AWS ML services teams and you will be involved in pre-silicon design, bringing new products / features to market, and many other exciting projects.

A background in machine learning and AI accelerators is preferred, but not required.

Explore the product and our history!

https : / / awsdocs-neuron.readthedocs-hosted.com / en / latest / neuron-guide / neuron-cc / index.html

https : / / aws.amazon.com / machine-learning / neuron /

https : / / github.com / aws / aws-neuron-sdk

https : / / www.amazon.science / how-silicon-innovation-became-the-secret-sauce-behind-awss-success

About the team

1. 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.

2. 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.

3. 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.

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

Toronto, ON, CAN

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

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, disability, age, or other legally protected status.

If you would like to request an accommodation, please notify your Recruiter.