About the position
Amazon Annapurna Labs team (our organization within AWS UC) is responsible for building innovation in silicon and software for our 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, software and operations. Because of our teams breadth of talent, we have been able to improve AWS cloud infrastructure in high-performance machine learning with AWS Neuron, Inferentia and Trainium ML chips, in networking and security with products such as AWS Nitro, Enhanced Network Adapter (ENA), and Elastic Fabric Adapter (EFA), and in computing with AWS Graviton and F1 EC2 instances. As a Sr. SDE you will work with external and internal customers to identify the main obstacles and the opportunities to accelerate their adoption of the Neuron technology.
Responsibilities
- Solve challenging technical problems, often ones not solved before, at every layer of the stack.
- Design, implement, test, deploy and maintain innovative software solutions to transform service performance, durability, cost, and security.
- Build high-quality, highly available, always-on products.
- Research implementations that deliver the best possible experiences for customers.
- 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.
- Collaborate closely with a cross-functional team comprised of compiler, hardware, and ML engineers.
- Work in a startup-like development environment, where you’re always working on the most important stuff.
Requirements
- 5+ years of non-internship professional software development experience
- 5+ years of programming with at least one software programming language experience
- 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Experience as a mentor, tech lead or leading an engineering team
- Hands-on technical experience working on the Generative AI space
Nice-to-haves
- Master's degree in computer science or equivalent
- 1+ years in machine learning or other computational modeling environments with an emphasis on building and optimizing models for diverse hardware platforms
Benefits
- Medical, financial, and/or other benefits
- Equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package
