Software Development Engineer, Neuron Collectives, Annapurna Labs

Amazon.com, Inc.
Cupertino, United States of America
2 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Compensation
$ 224K

Job location

Cupertino, United States of America

Tech stack

Artificial Intelligence
Amazon Web Services (AWS)
C++
Code Review
Data Centers
Software Design Patterns
Distributed Computing Environment
Distributed Systems
Embedded Software
Firmware
Machine Learning
Software Engineering
Systems Integration
Real Time Systems
Large Language Models
Information Technology
Build Process
Software Coding
Software Version Control

Job description

As a Neuron Collectives Software Developer, you will:

  • Enhance collective algorithms and topologies for optimal training performance
  • Use tools like Neuron Explorer to identify bottlenecks in compute and bus bandwidth utilization
  • Monitor and analyze processor, DMA, firmware, and workload metrics
  • Optimize collective operations to scale AI compute across the data center
  • Work closely with the hardware team to co-optimize software and Trainium silicon
  • Develop and optimize C/C++ implementations of collective communication patterns
  • Investigate and implement improvements for specific training topologies used by modern LLMs
  • Build and maintain analysis frameworks and automation solutions

The role offers opportunities to work on cutting-edge AI training hardware while contributing to one of Amazon's most critical initiatives.

A day in the life 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.

About the team Annapurna Labs, part of AWS, created Trainium as a purpose-built AI training chip to revolutionize machine learning at Amazon scale. The Neuron Collectives team owns the software stack that enables collective operations - the communication primitives that allow AI training to scale across thousands of chips in the data center. Our work is essential to training the frontier models that power AI today. We work closely with hardware teams to extract maximum performance from Trainium, ensuring that compute and interconnect bandwidth are fully utilized. Our team sits at the intersection of hardware, firmware, and distributed systems.

Requirements

Experience building complex software systems that have been successfully delivered to customers

  • Experience contributing to the architecture and design (architecture, design patterns, reliability and scaling) of new and current systems
  • Bachelor's degree in computer science or equivalent
  • Knowledge of engineering practices and patterns for the full software/hardware/networks development life cycle, including coding standards, code reviews, source control management, build processes, testing, certification, and livesite operations
  • Experience in development in the last 3 years, or experience in embedded development in C/C++, Master's degree in computer science or equivalent
  • Experience with hardware/software integration and real-time systems
  • Familiarity with collective communication algorithms (e.g., all-reduce, all-gather) or distributed training frameworks

Benefits & conditions

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, CA, Cupertino - 165,200.00 - 223,600.00 USD annually

About the company

Annapurna Labs is an integral part of AWS and develops hardware and software components that are critical building blocks for EC2 infrastructure. We specialize in designing software, systems and chips that optimize the AWS customer experience. The AWS Neuron Collectives team is seeking a Software Engineer to optimize collective operations for AWS Trainium. Trainium is one of Amazon's highest priority initiatives, powering the frontier AI models being trained today. Collectives are the critical operations that scale AI compute across the data center. You'll work in depth to optimize compute for the specific topologies used to train modern LLMs. Working closely with the hardware team, you'll push for maximum performance using C/C++, interfacing with DMA and firmware and investigating detailed topologies. You'll analyze current collective algorithms using publicly accessible tools like Neuron Explorer and optimize these to fully utilize compute and bus bandwidth to scale across the data center. This is a unique opportunity to impact how AI training runs at AWS scale, while growing your technical breadth and depth.

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