Ultra Low Power Machine Learning ASIC Design Engineer in San Diego, CA

$100K - $150K(Ladders Estimates)

Qualcomm Incorporated   •  

San Diego, CA 92101

Industry: Telecommunications & Hardware

  •  

5 - 7 years

Posted 29 days ago

Qualcomm is looking for an experienced digital designer to lead the development of digital subsystem for ultra-low power machine learning ASIC for deep learning tasks. You will work with exposure to various aspects of state of the art machine learning chip development for quantized neural network models. You will lead the development of digital architecture, RTL design and debug.

You will also have chance working on our next generation fingerprint sensor that embodies cutting edge technology to capture fingerprints using ultrasound waves. This technology allows phones to place fingerprint sensors underneath the display, which allows for larger screen sizes.

You will be involved in low power machine learning HW sub-system architecture definition and implementation, which include DSP and memory subsystems, HW accelerator and DMA sub-systems, ARM core integration etc. You will perform Verilog RTL design and chip integration at block and SoC level, work closely with design verification team and PD team in driving design to timing closure. Qualcomm is a company of inventors that unlocked 5G ushering in an age of rapid acceleration in connectivity and new possibilities that will transform industries, create jobs, and enrich lives. But this is just the beginning. It takes inventive minds with diverse skills, backgrounds, and cultures to transform 5Gs potential into world-changing technologies and products. This is the Invention Age and this is where you come in.

Qualcomm is looking for an experienced digital designer to lead the development of digital subsystem for ultra-low power machine learning ASIC for deep learning tasks. You will work with exposure to various aspects of state of the art machine learning chip development for quantized neural network models. You will lead the development of digital architecture, RTL design and debug.

You will also have chance working on our next generation fingerprint sensor that embodies cutting edge technology to capture fingerprints using ultrasound waves. This technology allows phones to place fingerprint sensors underneath the display, which allows for larger screen sizes.

You will be involved in low power machine learning HW sub-system architecture definition and implementation, which include DSP and memory subsystems, HW accelerator and DMA sub-systems, ARM core integration etc. You will perform Verilog RTL design and chip integration at block and SoC level, work closely with design verification team and PD team in driving design to timing closure.




All Qualcomm employees are expected to actively support diversity on their teams, and in the Company.


Minimum Qualifications


Bachelor's degree in Science, Engineering, or related field.

5+ years ASIC design, verification, or related work experience.

Bachelor's degree in Science, Engineering, or related field.

5+ years ASIC design, verification, or related work experience.


Preferred Qualifications


Master's, Electrical Engineering

Skilled in Verilog coding.

Expertise in logic synthesis

Experience with ULP SoC design methodology

Experience with the AHB bus protocol.

SoC integration experience.

Design Lead experience

General knowledge of DSP subsystem and architecture

General knowledge of machine learning HW accelerator design with in-memory or near-memory computing a plus

General knowledge of machine learning HW visualization technology a plus

Master's, Electrical Engineering

Skilled in Verilog coding.

Expertise in logic synthesis

Experience with ULP SoC design methodology

Experience with the AHB bus protocol.

SoC integration experience.

Design Lead experience

General knowledge of DSP subsystem and architecture

General knowledge of machine learning HW accelerator design with in-memory or near-memory computing a plus

General knowledge of machine learning HW visualization technology a plus


Education Requirements


Preferred: Master's, Electrical Engineering Required: Bachelor's degree in Science, Engineering, or related field.

Preferred: Master's, Electrical Engineering

Valid Through: 2019-10-17