We’re a stealth mode company building lightning fast interceptors to save lives. Backed by a16z.
About the role
Perception Pipeline Development: Develop robust real-time Deep Learning and Classical CV algorithms for classification, and tracking (e.g., YOLO, Transformer-based architectures) of highly dynamic objects. High-Speed State Estimation: Implement Visual-Inertial Odometry (VIO) and filtering techniques to estimate target 3D trajectories and "Time-to-Go" under high-G maneuvers.
What they're looking for
- Education: Master’s or PhD in Robotics, Computer Science, or Aerospace Engineering with a focus on Computer Vision or Autonomous Systems
- Dynamic Vision skills: Expert knowledge of object tracking (KCF, SORT, DeepSORT) and the geometry of moving camera platforms
- Real-Time Software: Proficiency in C++20 and CUDA for high-throughput image processing, and Python for training ML models
- Mathematics: Deep understanding of 3D geometry, Kalman Filtering (EKF/UKF), and the physics of relative motion
- EO/IR camera: Experience working with Long-Wave Infrared (LWIR) or Mid-Wave Infrared (MWIR) sensors
- Embedded Systems: Experience deploying models on NVIDIA Jetson Orin or FPGA-based vision processing
More about this role
Company Overview
We are a rapidly growing technology startup focused on delivering next-generation drones for security and safety applications. Our company vertically integrates hardware and software to create leading edge capabilities in the UAV space, with a focus on saving lives.
As a Computer Vision & Autonomy Engineer , you will be joining the team responsible for the design, development, and implementation of high-speed perception and autonomy stacks capable of identifying and tracking highly dynamic objects. You will solve the unique challenges of high-dynamic sensing , where relative velocities are extreme and the margin for error is zero.
Perception Pipeline Development: Develop robust real-time Deep Learning and Classical CV algorithms for classification, and tracking (e.g., YOLO, Transformer-based architectures) of highly dynamic objects.
High-Speed State Estimation: Implement Visual-Inertial Odometry (VIO) and filtering techniques to estimate target 3D trajectories and "Time-to-Go" under high-G maneuvers.
GPS denied perception stack: Create "GPS-denied" navigation solutions and anti-jamming vision pipelines that maintain autonomy when external signals are...
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