Robotics Engineer - Perception

Key Skills

Python Programming, SQL, Cloud computing

Job Description

Caterpillar’s Integrated Components and Solutions is seeking an experienced Robotics Engineer - Perception who is passionate about delivering autonomous vehicle solutions to production. This person is responsible for developing and demonstrating automation technologies, which are often used in conjunction with information systems, remote control, semi-autonomous, and fully autonomous machine control systems. This is an ideal opportunity for someone with experience in developing perception algorithms and techniques and implementing production quality software in C/C++/Python.

Responsibilities:

• Research and develop perception algorithms for personnel detect, object detection, tracking, classification, terrain mapping, localization and others.
• Benchmark and Tune the Perception/Computer Vison Algorithms and the Hardware Accelerators for performance and quality KPIs.
• Participate in R&D programs through entire lifecycle, from initial inception through production and Research and develop new technology in perception
• Work closely with diverse groups across Caterpillar and contribute towards overall Autonomous Vehicles Architecture taking safety into consideration
• Develop production quality code and own your algorithms from design to production

  Run simulation for perception algorithm development and test various scenarios

  Develop deployable code that will run on resource constrained platforms on mining and construction equipment.

• Develop simulation environments, models, assets, and work with the team to setup CI pipelines

Desired Qualifications:

• BE/ME/PhD in Computer Engineering, Robotics Engineering, Mechatronics, Computer Science, Electrical Engineering, Robotics or a related field.
• Sound knowledge of machine learning/deep learning algorithms, principles and their application
• Experience working with Convolutional Neural Networks.
• 2+ yrs exp in deep learning creating and testing systems and networks including experience with GPU platforms, in particular object detection and image segmentation networks.
• Experience with both classical computer vision techniques as well as machine learning/ deep learning techniques.
• Experience with classification, detection, segmentation(semantic/panoptic), localization and tracking.
• Experience in analyzing and developing performance metrics for computer vision algorithms and applications.
• Experience in ROS, Tensorflow, Keras, Caffe, TensorRT, DeepStream, Docker, PCL
• Familiarity with the PyTorch deep learning framework.
• Good understanding of object detection and models like YOLO, RCNN, and Mask-RCNN, etc.
• Significant working knowledge of Python, including best practices for testing, documentation, and version control using Git
• Strong programming skills with C/C++ using Linux OS, and middle ware such as ROS/ROS2 and DDS.
• The ablity to create and benchmark the performance of different types of deep learning networks to understand resource requirements
• Creation and management of large machine learning pipeline and datasets including framework for tagging, web-based tools for crawling and sorting the data.
• Familiarity with Lidar, Radar and Camera Data collection and management framework.
• Ability to analyse the performance of different types of deep learning networks on various GPUs
• Experience on programming of Computer vision/perception Systems software, sensor fusion that integrates with perception sensors such as IMU, GPS, Stereo Cameras, LiDAR, RADAR.
• Proficient in anyone of PyTorch/Tensorflow/keras frameworks in Python/C++
• Hands-on hyperparameter tuning.
• Good knowledge/experience with CUDA/CuDNN tools.
• Experience on ROS (Rosbag and RViz) for simulation with perception
• Strong math background and strong computational geometry skills
• Knowledge on embedded systems (NVIDIA Jetson, Xavier) & Xilinx
• Knowledge on Dynamics & control, modelling & simulation, and algorithm validation
• Experience with ADAS would be an advantage.
• Hands-on Experience with MATLab / FPGA / ARM processor would be an advantage
• Knowledge of GPU or parallel computing platforms like CUDA.
• Experience with ARM CPU architecture and hardware considerations (memory controllers, buses, caches, etc.).
• Understanding of principles of RADARs and LiDARs.
• Excellent analytical, communication and interpersonal skills.

Preferred Qualifications:

• Experience with C++ 11/14/17 and python
• Experience in implementing State-Of-The-Art(SOTA) models in practice
• Publications in CVPR/NIPS/ICML/ICLR would be an added advantage.