Senior Computer Vision Engineer (Autonomous Driving)
Mountain View, United States
42dotFull-time
We are looking for the best

As a Senior Computer Vision Research Engineer at 42dot, you will focus on researching and developing advanced autonomous driving technologies. Utilizing sophisticated computer vision and machine learning techniques, you will process various visual data acquired from autonomous vehicles and implement human-level autonomous driving perception capabilities.

Responsibilities

  • Conduct research and develop 3D computer vision and machine learning algorithms for integrating autonomous driving technology
  • Perform 3D shape modeling and processing tasks
  • Implement object pose estimation and tracking algorithms
  • Develop efficient and scalable vision solutions
  • Explore the intersection of vision and robotics
  • Work on low-level and physics-based vision algorithms

Qualifications

  • Minimum of 7 years of relevant experience
  • Master's or PhD degree, or equivalent experience, in computer vision, robotics, or machine learning, or a related field
  • Theoretical and practical knowledge in computer vision and machine learning
  • Excellent programming skills (C/C++, Python, etc.)

Preferred Qualifications

  • Research and development experience in autonomous driving and robotics
  • Experience with development using various sensors such as GPS, IMU, cameras, and LIDAR
  • Experience in developing VR/AR applications
  • Development experience in parallel programming and system optimization
  • Published works and academic activities in related fields (e.g., CVPR, ICCV, ECCV, IJCV, TIP, TPAMI)

Interview Process

  • Application Review - Coding Test - 1st Interview - 2nd Interview - Offer
  • The process may vary by position and is subject to change.
  • Schedule and results will be communicated via the email provided in your application.
Please refer to the videos from KCCV 2022 and UMOS Day 2021 for insights into 42dot Autonomous Driving, our autonomous driving AI software.

Please upload all submission files in PDF format.

Please review the following information before applying.

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