Software Dev Engineer, Edge Technology
Amazon • Sunnyvale, California, United States
No Relocation
Posted: July 8, 2026
Additional Content
Description
- Amazon Lab126 is an inventive research and development company that designs and engineers high-profile consumer electronics. Lab126 began in 2004 as a subsidiary of Amazon.com, Inc., originally creating
Description
- Amazon Lab126 is an inventive research and development company that designs and engineers high-profile consumer electronics. Lab126 began in 2004 as a subsidiary of Amazon.com, Inc., originally creating the best-selling Kindle family of products. Since then, we have produced devices like Fire tablets, Fire TV, Echo Show. The Amazon Devices group delivers delightfully unique Amazon experiences, giving customers instant access to everything, digital or physical. Key job responsibilities In this role, you will: - Create world class software and firmware to customer features on Amazon devices and services. - Adopt and drive latest AI tools to enhance the pace of delivery of a feature. - Interact with cross-functional engineering teams across the company - Dive into and take ownership for critical design issues involving multi radio coexistence, antenna configuration and overall system performance. - Participate in design reviews - Influence system architecture and the selection of chipsets. - Collaborate with silicon partners to define and optimize HW/SW architecture and implementation - Address all aspects of technology readiness, including manufacturability - Help build robust methodology and processes to deliver technology to products
Basic Qualifications
- - 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 - Knowledge of ARM CPUs - Knowledge of Machine Learning and LLM fundamentals, including transformer architecture, training/inference lifecycles, and optimization techniques