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Wireless Science Manager, Device Connectivity

External
Amazon.com Services LLC logoAmazon.com · Sunnyvale, CA
Full-timeOn-site1d ago
AWSMachine Learning
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Requirements

  • 5+ years of scientists or machine learning engineers management experience
  • Knowledge of machine learning approaches and algorithms
  • 7+ years of wireless communications systems and implementation experience
  • Experience building machine learning models or developing algorithms for business application
  • Experience building complex highly-scalable systems that involve predictive models or applications of machine learning
  • Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
  • USA, CA, Sunnyvale - 211,400.00 - 286,000.00 USD annually

Additional Information

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, and Amazon Echo. What will you help us create? The Wireless Applied Science Manager will manage the Wireless Science team. You will manage the recruitment, selection and retention of the team as we continue to grow our business. You will be responsible for the Wireless Algorithm and science development and will be hands on with the team throughout the development process from concept through design, test, and into mass-production support. You are ultimately accountable for delivering the performance and quality. Key job responsibilities In this role you will: - Recruit, manage and maintain a world class Wireless Communications Systems team - Attend and run cross functional engineering meetings - Dive into and take ownership for critical design issues - Lead design reviews and report on status of development, quality, operations and system performance to management - Build design processes to continuously improve performance and quality


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