SDE II, ML Infra Services, Annapurna Labs

Amazon.com, Inc.
Seattle, United States of America
12 days ago

Role details

Contract type
Internship / Graduate position
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Intermediate
Compensation
$ 194K

Job location

Remote
Seattle, United States of America

Tech stack

Java
JavaScript
Adobe InDesign
Amazon Web Services (AWS)
Amazon Web Services (AWS)
Amazon Web Services (AWS)
Big Data
Code Generation
Profiling
Code Review
Computer Programming
Software Design Patterns
Amazon DynamoDB
Integrated Development Environments
Python
Machine Learning
Software Architecture
Azure
Software Engineering
TypeScript
AI Infrastructure
Session Description Protocol Security Descriptions (SDES)
Kubernetes
Information Technology
Build Process
Machine Learning Operations
Functional Programming
Software Coding
Amazon Web Services (AWS)
Software Version Control
Docker

Job description

This engineer will lead the design and implementation of ML infrastructure platform, building systems for capacity management, workload scheduling, and fleet orchestration across ML accelerators. They will work with ML scientists, training infrastructure engineers, hardware teams, and internal customers to ensure the ML Infra service delivers seamless ML Accelerator access with low wait times, high utilization, and zero-config deployment from various environments.

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

  • High-impact, high-visibility: You'll directly accelerate every Neuron team's ability to ship - your work multiplies the output of 100+ engineers
  • Greenfield opportunities: We're actively building new capabilities with significant design ownership for SDEs
  • Small, senior team: where every person owns major components and drives architectural decisions
  • AI infrastructure: Work at the intersection of Kubernetes, custom silicon, and large-scale ML workloads

Diverse Experiences We value diverse experiences and non-traditional career paths. If your career is just starting or includes alternative experiences, we encourage you to apply.

Inclusive Team Culture Our employee-led affinity groups foster inclusion. Events like CORE and AmazeCon inspire us to embrace our uniqueness.

Work/Life Balance We strive for flexibility as part of our working culture, supporting you both at work and at home.

Mentorship & Career Growth We offer knowledge-sharing, mentorship, and one-on-one code reviews to help you grow as a professional.

Hybrid Work This role is onsite, with flexibility to work remotely when you're unable to make it into the office.

Requirements

AWS Neuron is the complete software stack for the AWS Inferentia and Trainium cloud-scale machine learning accelerators and the Trn1 and Inf1 servers that use them. This position is for a Software Engineer that will lead the development of machine learning tools to run, optimize, and analyze machine learning workloads. This candidate must have had experience leading machine learning tool projects, preferably starting from architecture through several generations of delivery to customers. Deep knowledge of profiling and optimization, resource management, scheduling, code generation are needed. The ideal candidate will have worked on new instruction set architectures, which may include CPU, NPU, GPU and other forms of compute., 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, 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
  • Experience taking a leading role in building complex software or computing infrastructure that has been successfully delivered to customers
  • Experience with AWS Services including EC2, Lambda, S3, DynamoDB, SQS
  • Experience in Kubernetes, Docker or containers ecosystem, or experience managing full application stacks from the OS up through custom applications and experience in any Bigdata architecture
  • Experience with version control systems and CI/CD pipeline implementation
  • Strong proficiency in Go/Java, Python, and Javascript/Typescript
  • Application and kernel performance profiling and optimization
  • Proficiency in integrated software/hardware performance analysis and optimization
  • Experience designing and operating production services

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, WA, Seattle - 143,700.00 - 194,400.00 USD annually

About the company

Annapurna Labs was a startup company acquired by AWS in 2015, and is now fully integrated. If AWS is an infrastructure company, then think Annapurna Labs as the infrastructure provider of AWS. Our org covers multiple disciplines including silicon engineering, hardware design and verification, software, and operations. AWS Nitro, ENA, EFA, Graviton and F1 EC2 Instances, AWS Neuron, Inferentia and Trainium ML Accelerators, and in storage with scalable NVMe, are some of the products we have delivered, over the last few years.

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