Sensor Calibration Engineer

23 hours ago


Bengaluru, Karnataka, India Ola Full time

Job Overview

We are seeking a Sensor Calibration Engineer to develop, optimize, and automate calibration processes for camera, radar, IMU, and LiDAR sensors on vehicles, focusing on 3D depth estimation and multi-sensor fusion. The ideal candidate will have expertise in sensor error quantification, C/C++, Python, ROS, and PCL. This role involves cross-functional collaboration to ensure precise sensor alignment and integration with ADAS.

Key Responsibilities:

  • Develop and refine intrinsic/extrinsic calibration for camera, radar, IMU, and LiDAR.
  • Implement 3D depth estimation techniques and automate multi-sensor calibration pipelines.
  • Write C/C++ and Python scripts for automation and real-time sensor data processing.
  • Conduct error quantification, drift detection, and system performance analysis.
  • Collaborate with hardware and perception teams to integrate calibration workflows.
  • Design and execute testing and validation in lab and real-world environments

Required Skills:

  • Proficiency in C/C++, Python, ROS, OpenCV, PCL, and Eigen.
  • Strong understanding of geometric computer vision, sensor fusion, and error modeling.
  • Experience with SLAM, depth estimation, and coordinate transformations.
  • Knowledge of deep learning-based calibration (preferred).
  • Hands on experience on different interfaces like Ethernet, USB, CAN , RS232
  • Hands on experience on Microcontroller & Microprocessor, ARM based system development

Required Qualifications:

  • Bachelor's or Master's in Electrical Engineering, Robotics, Computer Science, or related field.
  • 3+ years of experience in sensor calibration and multi-sensor fusion.
  • Proficiency in C/C++, Python, ROS, OpenCV, PCL, Eigen & Linux platform
  • Strong understanding of geometric computer vision, sensor fusion, and error modeling.
  • Experience with SLAM, depth estimation, and coordinate transformations.
  • Knowledge of deep learning-based calibration (preferred).


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