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Senior Computer Vision and Machine Learning Engineer

2 months ago


San Francisco, California, United States Plato Full time
About Plato

We are a pioneering technology company specializing in perception systems for autonomy. Our team of experts is based in the San Francisco Bay Area and is dedicated to developing cutting-edge software solutions for location improvement and safety.

Our mission is to push the boundaries of computer vision and machine learning, and our team is comprised of faculty entrepreneurs and industry veterans with a proven track record of success. We are committed to delivering innovative solutions that meet the needs of our clients.

Job Summary

We are seeking a highly skilled Senior Computer Vision and Machine Learning Engineer to join our team. The successful candidate will have a strong background in computer vision and machine learning, and will be responsible for developing and evaluating advanced image processing and computer vision algorithms.

Responsibilities
  • Design, develop, and evaluate advanced image processing and computer vision algorithms for a real-time computer vision pipeline.
  • Lead the development of state-of-the-art deep learning networks and architectures.
  • Optimize algorithm performance across a wide range of development platforms and embedded systems.
  • Develop evaluation scripts to process large data and accurately measure algorithmic and end-to-end performance.
Requirements
  • PhD in Computer Vision and Machine Learning with 4+ years of industry experience or MS in Computer Vision and Machine Learning with 5+ years of industry experience.
  • Strong programming skills in Python and C++.
  • Experience with OpenCV, PIL, and other image processing libraries.
  • Experience with deep learning frameworks such as PyTorch, TensorFlow, and ONNX.
  • Excellent problem-solving skills and ability to work in a fast-paced environment.
Preferred Qualifications
  • Prior experience with multi-sensor calibration and multi-view geometry.
  • Hands-on experience with different neural network architectures and common datasets.
  • Solid software engineering foundation and a commitment to writing clean, well-architected code.
  • Familiarity with various physical aspects of sensors, including cameras and Lidars.