JOB POSTING INFORMATION
Position Type:	Professional Experience Year Co-op (PEY Co-op: 12-16 months)
Job Title:	AWS Neuron Performance Modeling / Tools Software Engineer Co-op
Job Location:	Toronto, ON
Job Location Type:	Hybrid (minimum 3 days a week in office at 18 York Street)
If working on site, can you provide a copy of your COVID-19 safety protocols?:	Yes
Number of Positions:	1
Salary:	$0.00 hourly for 0.0 hours per week
Start Date:	05/06/2024
End Date:	08/29/2025
Job Function:	Engineering
Job 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 is 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 looking for students interested in contributing to a performance modeling and tools ecosystem to gain in-depth automated insights into deep-learning model performance on AWS Inferentia and Trainium. As a performance modeling & tools engineer on the Neuron team, you will be supporting the development of models to help what-if analyses, as well as guide targets for model performance. You will also develop tools to visualize and identify bottlenecks in deep learning workloads. You will architect and implement business-critical features, and be mentored by a brilliant team of experienced engineers.   About Us   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 14 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-live 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 Opportunities   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 and thorough, but kind, code reviews. 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   Join us today and shape the future of one of AWS fastest growing products! 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.
Job Requirements:	Preferred Qualifications • B.S. Computer Science, Computer Engineering or related technical field • Proficiency with one or more of the following programming languages: C, C++, or Python • Strong background in data structures and algorithms • Exposure to front-end ML frameworks (i.e. PyTorch, TensorFlow, etc.) is an asset • Understanding of deep-learning workloads and operators is an asset • Experience with Javascript, and React is an asset • Experience with Instruction Set Architectures is an asset
Preferred Disciplines:	Computer Engineering Computer Science Electrical Engineering Engineering Science (Electrical and Computer) Engineering Science (Machine Intelligence) Engineering Science (Robotics)
All Co-op programs:	No
Targeted Co-op Programs:	Targeted Programs Professional Experience Year Co-op (12 - 16 months)

APPLICATION INFORMATION
Application Deadline:	Oct 6, 2023 11:59 PM
Application Receipt Procedure:	Online via system
U of T Job Coordinator:	Nabeela Rahman

ORGANIZATION INFORMATION
Organization:	Amazon
Division:	AWS Neuron

ADDITIONAL INFORMATION
Length of Workterm:	FLEXIBLE PEY Co-op: 12-16 months (range)