Computer Vision Engineer

About Us:
STARK is a new kind of defence technology company revolutionizing the way autonomous systems are deployed across multiple domains. We design, develop and manufacture high performance unmanned systems that are software-defined, mass-scalable, and cost effective. This provides our operators with a decisive edge in highly contested environments.
We’re focused on delivering deployable, high-performance systems - not future promises. In a time of rising threats, STARK is bolstering the technological edge of NATO Allies and their Partners to deter aggression and defend Europe - today.

Your mission:
You will be developing cutting-edge Computer Vision solutions and algorithms for our autonomous vehicles, bringing these onto our hardware in real time.

Responsibilities:
• Design and develop object detection and tracking pipelines for guidance and terminal guidance    
• Work with frame-to-frame tracking, re-detection logic, and confidence estimation to prevent tracker drift or false lock
• Develop approaches to separate targets from shadows, reflections, terrain, and background noise    
• Work with multi-sensor vision (daylight, night, thermal / IR), including alignment, synchronization, and fusion    
• Provide uncertainty and confidence metrics to downstream guidance and control systems    
• Integrate vision outputs into the guidance loop, considering latency, update rate, and coordinate frames
• Optimize and deploy models on edge hardware (e.g. Jetson-class devices)    
• Analyze flight logs, investigate failure cases, and improve robustness based on real data    
• Collaborate closely with GNC, autonomy, and embedded teams during development and flight testing

Qualifications:
• Strong background in computer vision (classical + deep learning)
• Experience with object tracking beyond basic APIs (understanding drift, re-initialization, failure modes)
• Hands-on experience with video-based systems in real-world conditions
• Solid programming skills in Python 
• Experience deploying or optimizing models for real-time / edge environments
• Ability to reason about uncertainty, confidence, and system-level impact

Nice to have:
• Experience with multi-sensor systems (day / night / thermal)
• Background in robotics, UAVs, or autonomous system
• Familiarity with ROS / ROS2 / C++
• Experience with Kalman filters or sensor fusion
• Knowledge of ONNX, TensorRT, CUDA
• Experience working with GNSS-denied or degraded environments