The Annapurna Labs team at Amazon Web Services (AWS) builds AWS Neuron, the
software development kit used to accelerate deep learning and GenAI workloads on
Amazon’s custom machine learning accelerators, Inferentia and Trainium.
The Acceleration Kernel Library team is at the forefront of maximizing
performance for AWS's custom ML accelerators. Working at the hardware-software
boundary, our engineers craft high-performance kernels for ML functions,
ensuring every FLOP counts in delivering optimal performance for our customers'
demanding workloads. We combine deep hardware knowledge with ML expertise to
push the boundaries of what's possible in AI acceleration.
The AWS Neuron SDK, developed by the Annapurna Labs team at AWS, is the backbone
for accelerating deep learning and GenAI workloads on Amazon's Inferentia and
Trainium ML accelerators. This comprehensive toolkit includes an ML compiler,
runtime, and application framework that seamlessly integrates with popular ML
frameworks like PyTorch, enabling unparalleled ML inference and training
performance.
As part of the broader Neuron Compiler organization, our team works across
multiple technology layers - from frameworks and compilers to runtime and
collectives. We not only optimize current performance but also contribute to
future architecture designs, working closely with customers to enable their
models and ensure optimal performance. This role offers a unique opportunity to
work at the intersection of machine learning, high-performance computing, and
distributed architectures, where you'll help shape the future of AI acceleration
technology
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. The team works closely with customers on their model enablement,
providing direct support and optimization expertise to ensure their machine
learning workloads achieve optimal performance on AWS ML accelerators.
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
Key job responsibilities
Our kernel engineers collaborate across compiler, runtime, framework, and
hardware teams to optimize machine learning workloads for our global customer
base. Working at the intersection of software, hardware, and machine learning
systems, you'll bring expertise in low-level optimization, system architecture,
and ML model acceleration. In this role, you will:
- Design and implement high-performance compute kernels for ML operations,
leveraging the Neuron architecture and programming models
- Analyze and optimize kernel-level performance across multiple generations of
Neuron hardware
- Conduct detailed performance analysis using profiling tools to identify and
resolve bottlenecks
- Implement compiler optimizations such as fusion, sharding, tiling, and
scheduling
- Work directly with customers to enable and optimize their ML models on AWS
accelerators
- Collaborate across teams to develop innovative kernel optimization techniques
A day in the life
As you design and code solutions to help our team drive efficiencies in software
architecture, you’ll create metrics, implement automation and other
improvements, and resolve the root cause of software defects. You’ll also:
Build high-impact solutions to deliver to our large customer base.
Participate in design discussions, code review, and communicate with internal
and external stakeholders.
Work cross-functionally to help drive business decisions with your technical
input.
Work in a startup-like development environment, where you’re always working on
the most important stuff.
About the team
1. Why AWS
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted
cloud platform. We pioneered cloud computing and never stopped innovating —
that’s why customers from the most successful startups to Global 500 companies
trust our robust suite of products and services to power their businesses.
2. 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.
3. 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.
4. 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.
5. Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the
qualifications and skills listed in the job description, we encourage candidates
to apply. If your career is just starting, hasn’t followed a traditional path,
or includes alternative experiences, don’t let it stop you from applying.
