The Amazon Devices team designs and engineers high-profile consumer electronics, including the best-selling Kindle family of products. We have also produced groundbreaking devices like Fire tablets, Fire TV, Amazon Dash, and Amazon Echo. What will you help us create?

Work hard. Have fun. Make history.

The Role

We are looking for exceptional SDE to join the DeviceOS team to design, build, and support scalable solutions to run best-in-class models on our devices. In this role you are responsible for leading the development of OS stack, to advance the state of the art with conversational software solutions. You will solve complex problems in hybrid computing technologies, and build solutions to leverage heterogeneous compute sources to achieve optimal solutions for compute work load acceleration on the device. You will drive the system architecture, and spearhead the best practices that enable a quality infrastructure. In this role you will closely with HW teams, Deep Learning scientists, and other cross disciplinary teams to analyze requirements and customer experiences, research existing technologies, and build proof-of-concepts for quick validations of new approaches.

You will dive into an ambiguous problem spaces and meticulously distill out design choices, trade-offs, and priorities. You will Investigate, prototype and deliver new and innovative system solutions, participate in design reviews, API development, and documentation

You love to share best practices, influence and align teams, and be a technical ambassador for software reuse across the wider Amazon organization.

BASIC QUALIFICATIONS

- 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
- Experience as a mentor, tech lead or leading an engineering team

PREFERRED QUALIFICATIONS

- 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Knowledge of neural deep learning methods and machine learning
- Knowledge of HW accelerators, preferably for machine learning workloads
- Working knowledge of ML model optimizations on HW accelerators.

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.