Core Responsibilities

1. Technical Leadership & Roadmap Strategy

• Define the Vision: Outline and execute the technical roadmap for the perception stack, transitioning from theoretical research to field-deployable military solutions.

• Algorithm Selection: Make high-stakes architectural decisions regarding algorithm selection. You must balance state-of-the-art accuracy with the strict computational constraints (SWaP—Size, Weight, and Power) of drone hardware.

• Team Management: Mentor, grow, and manage a team of CV and Robotics engineers. Foster a culture of mathematical rigor and engineering excellence.

2. Advanced Sensor Fusion & Detection

• Multi-Modal Fusion: Architect sensor fusion frameworks integrating RGB, LiDAR, and Thermal/IR imaging.

• Adversarial Detection: Develop novel algorithms to detect personnel and equipment employing active camouflage techniques (e.g., ghillie suits, camouflage nets, environmental blending) where standard RGB inference fails.

• Geometric Understanding: Implement systems that can instantly map and understand complex, fast-changing 3D geometries to distinguish between navigable terrain, blocked routes, and cover.

3. Theoretical Application

• Apply deep theoretical knowledge of mathematics and physics to model environmental noise, sensor uncertainty, and dynamic object tracking.

• Drive research into novel deep learning architectures and probabilistic robotics to solve "edge cases" that are common in combat scenarios.

The Technical Challenge

To succeed in this role, you must be energized by the following specific problems:

• Beyond RGB: Enemy combatants use camouflage to blend into the spectrum. You must leverage thermal signatures and LiDAR point-cloud anomalies to detect what the eye cannot see.

• Dynamic Geometry: The battlefield is not static. Debris, smoke, and destruction alter the environment in real-time. Your perception module must identify clear vs. blocked routes instantly to ensure autonomous maneuverability.

• Resource Constraints: You are not running on a server farm. Your algorithms must be highly optimized to run on edge computing devices (e.g., NVIDIA Jetson, FPGA) without sacrificing mission-critical latency.

Must-Have Qualifications

• Education: MSc or PhD in Robotics, Computer Science, Mathematics, Physics, or a related field. Deep theoretical understanding of the underlying math is non-negotiable.

• Industry Experience: Minimum 5+ years of experience in the robotics industry (experience with purely academic research is insufficient without industrial application).

• Leadership: Proven experience leading technical teams and managing product roadmaps.

• Computer Vision & Sensor Fusion:

  • Mastery of State-of-the-Art Computer Vision algorithms (Object Detection, Semantic Segmentation, Tracking).

  • Deep experience with Sensor Fusion techniques (Kalman Filters, Particle Filters, Bayesian networks) merging data from LiDAR, Thermal, and Visual sources.

• Robotics Theory: Strong background in SLAM (Simultaneous Localization and Mapping), Visual Odometry, and 3D reconstruction.

Preferred Qualifications

• Experience with military or dual-use technologies.

• Proficiency in C++ and Python within a ROS2 environment.

• Experience optimizing neural networks for embedded hardware (TensorRT, CUDA).

• Publications in top-tier robotics/vision conferences (CVPR, ICRA, IROS).

Why Join Us?

• Impact: Your work will directly influence the safety and efficacy of autonomous systems in critical situations.

• Complexity: You will work on problems that standard commercial robotics companies do not face.

• Resources: Access to top-tier hardware, sensors, and testing environments.