Ambarella Corp.

Ambarella Corp.

Staff System Software Engineer - Embedded AI & Algorithm

US Headquarters · Staff+ · Full-time

Sponsorship not specified$160k-$183kDetected 32 days ago
PythonC++AlgorithmsMachine LearningDeep LearningTensorFlowPyTorchComputer VisionResearch

About the role

  • AI Vision Processors For Edge Applications Our solutions make cameras smarter by extracting valuable data from high-resolution video streams.
  • Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.
  • The successful candidate will have the opportunity to convert to a full-time regular position.

Responsibilities

  • We offer a unique opportunity to push the envelope of algorithm design and collaborate across a broad set of disciplines in a small-company environment.

Requirements

  • Master or PHD Degree in CS/EE
  • 8 years of experience with Edge Devices
  • Our target applications include autonomous vehicles, intelligent video surveillance, self-flying drones, smart wearable cameras, 360-degree immersive video, and more.

Nice to have

  • Experience in Image Quality Tuning, Image processing algorithm, and Image Processing Pipeline is a plus.

Compensation

  • Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.

Benefits

  • AI Vision Processors For Edge Applications
  • At Ambarella, we are looking for talented team members to help us deliver our advanced computer vision algorithms to tomorrow's intelligent video products.
  • If you enjoy great rewards, Ambarella has it all, great health, and welfare benefits!
  • System Software Algorithm engineers at Ambarella research and develop next-generation computer vision algorithms in a wide variety of our future products.
  • Develop ML and computer vision algorithms/systems.
  • Training and optimization of deep learning/ML based computer vision algorithm for edge devices.

This listing is sourced directly from Ambarella Corp.'s careers page and normalized into a canonical job model.