Sr Hardware Development Manager, Amazon Industrial Robotics

Amazon.com, Inc.
North Reading, MA, United States
7 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Compensation
$179,700.0 - $243,100.0
Working hours
Regular working hours
Job source

Tech stack

Microsoft Word Microsoft Excel AutoCAD Computing Platforms Computer Engineering Firmware Hardware Design Microsoft Project Microsoft Visio Microsoft PowerPoint Systems Architecture Systems Integration

Job description

As a Sr Hardware Development Manager, you will be responsible for developing complex computing and firmware systems that power our robotic platforms. You will lead a team of engineers focused on system architecture, firmware development, and embedded systems integration while implementing robust development processes and technical standards., * Lead a team of hardware, firmware, and embedded systems engineers

  • Implement computing architecture standards and firmware development practices
  • Contribute to technical roadmaps for next-generation robotics computing platforms
  • Design and implement robust, scalable firmware solutions
  • Execute development processes for safety-critical embedded systems
  • Collaborate with robotics, controls, and software teams to deliver integrated solutions
  • Support architecture decisions for complex robotics systems
  • Implement firmware development strategies
  • Ensure reliable, maintainable, and scalable embedded solutions
  • Follow technical standards for robotics computing platforms
  • Drive innovation in real-time computing and control systems

Requirements

  • 5+ years of manufacturing, process, industrial engineering experience
  • 10+ years of engineering team management experience
  • Bachelor’s degree in Electronic Engineering, Computer Engineering, or a related field
  • Experience in engineering team management
  • Experience in manufacturing, process, or industrial engineering
  • Experience developing and testing mechanical robotics equipment
  • Experience in system-level integration
  • Experience with DFx (cost, test, manufacturing), * Master’s degree in Mechanical or Electrical Engineering or a related field
  • Knowledge of MS Excel, AutoCAD, MS Project, and software for technical document writing such as Visio, Word, or PowerPoint
  • Experience in technical leadership of development, testing, and implementation of large-scale, complex technology projects
  • Experience working as a technical lead

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, MA, N.Reading - 179,700.00 - 243,100.00 USD annually

About the company

Amazon is seeking exceptional talent to help develop the next generation of advanced robotics systems that will transform automation at Amazon’s scale. We’re building revolutionary robotic systems that combine cutting-edge AI, sophisticated control systems, and advanced mechanical design to create adaptable automation solutions capable of working safely alongside humans in dynamic environments. This is a unique opportunity to shape the future of robotics and automation at an unprecedented scale, working with world-class teams pushing the boundaries of what’s possible in robotic dexterous manipulation, locomotion, and human-robot interaction. This role presents an opportunity to shape the future of robotics through innovative applications of deep learning and large language models.

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