Sr. Software Development Manager
4 weeks ago
The Team: The Amazon Annapurna Labs team is 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: As a Manager III on the AWS Neuron team, you'll be leading a team of compiler engineers through developing, deploying, and scaling a compiler targeting AWS Inferentia and Trainium. 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 vision and technical communication skills as a hands-on partner to AWS ML services teams, to be involved in pre-silicon design, bring new products/optimizations/features to market, and many other exciting projects to ensure the Neuron SDK exceeds our customers' needs of high performance, low cost, and ease of use.
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 Toronto.
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.
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. 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:
Toronto, ON, CAN
BASIC QUALIFICATIONS
- - 6+ years of engineering team management experience- - 8+ years of working directly within engineering teams experience
- - 6+ years of designing or architecting (design patterns, reliability and scaling) of new and existing systems experience
- - Experience partnering with product or program management teams
- - Excellent software design fundamentals, knowledge of software engineering principles, and a deep understanding of compilers (resource management, instruction scheduling, code generation, and compute graph optimization
PREFERRED QUALIFICATIONS
- - M.S. or Ph.D. in Computer Science or related technical field.- - Experience with toolchains (LLVM, GCC) and code generation techniques for new hardware.
- - Knowledge of compiler internals from front end to run-time environment with emphasis on AI acceleration.
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