Computer Vision Engineer – Autonomy & Perception

Sourced from feeny.ai

Pivotal is seeking a Computer Vision Engineer to build next-generation perception systems for its autonomous eVTOL aircraft, including the Helix platform. You will design and deploy computer vision and deep learning algorithms for object detection, tracking, visual localization, and sensor fusion in GPS-denied environments. The role spans perception pipelines, visual-inertial odometry, SLAM, camera calibration, and edge AI deployment in collaboration with autonomy, GNC, and flight software teams.

• Design and develop perception systems for autonomous aerial platforms in GPS-denied and contested environments
• Implement object detection, classification, segmentation, and tracking using RGB, thermal, and multimodal sensor data
• Develop visual-inertial odometry, localization, mapping, and SLAM algorithms
• Fuse camera, IMU, GPS, lidar, and radar data for robust state estimation
• Train and deploy deep learning models for onboard perception and optimize for real-time edge inference
• Integrate and calibrate diverse camera systems including RGB, stereo, fisheye, thermal, and event-based cameras
• Build simulation and testing frameworks and support flight test validation

• Bachelor's degree in Computer Science, Robotics, Electrical Engineering, Aerospace Engineering, or related field
• 2–4 years of industry experience in computer vision, robotics, machine learning, or autonomous systems (or Master's with 1–2 years)
• Strong proficiency in C++, Python, or Rust
• Experience with OpenCV and modern computer vision frameworks
• Experience with PyTorch, TensorFlow, or similar ML frameworks
• Understanding of image processing, geometric vision, and camera systems
• Experience with object detection, tracking, segmentation, and ML-based perception
• Familiarity with sensor fusion and state estimation
• Experience with ROS/ROS2 or similar robotics middleware
• Software development in Linux environments

• Master's or PhD in Computer Vision, Robotics, Machine Learning, or related field
• Experience with autonomous aircraft, UAVs, robotics, or aerospace systems
• Experience with visual SLAM, visual-inertial odometry, or localization
• Knowledge of camera calibration, multi-camera systems, and geometric computer vision
• Experience integrating lidar, radar, thermal cameras, and inertial sensors
• Experience deploying AI models on NVIDIA Jetson or similar edge hardware
• Familiarity with Gazebo, Isaac Sim, AirSim, or equivalent simulation environments
• Contributions to open-source robotics, autonomy, or computer vision projects