Computer Vision & Autonomy Engineer

Computer Vision & Autonomy Engineer

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 compromised.

• Guidance Logic:
  Design "Vision-Based Pursuit" laws and Proportional Navigation (PN) enhancements that translate visual target states into actionable steering commands.

• Real-time Deployment:
  Optimize algorithms for ultra-low latency execution on low-power devices, ensuring the "sensor-to-actuator" delay is minimized.

• Deterministic Benchmarking:
  Profile and eliminate "long-tail" latency spikes in the autonomy stack to ensure a deterministic sensor-to-actuator response time.

• 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.

• High-Fidelity Simulation:
  Proficiency in NVIDIA Isaac Sim, Unreal Engine 5, or Gazebo to generate synthetic data for rare "corner-case" scenarios.

Control Integration:
Understanding of how perception latency affects the stability of flight control loops.