Software Engineer I, Perception (New Grad)

True Anomaly delivers autonomous spacecraft, advanced payloads, mission software, and space-based interceptors for space superiority. The Software Engineer I, Perception will develop hybrid computer vision and deep learning perception systems for autonomous spacecraft, including tracking, coordinate transformations, synthetic data generation, and onboard deployment. This entry-level role combines classical robotics perception with modern machine learning under strict compute and power constraints.

Responsibilities:

• Implement classical tracking algorithms: Extended Kalman Filters for state estimation, Hungarian algorithm for data association, track management logic (tentative/confirmed/coasted tracks)
• Train neural networks for detection and classification: YOLO for object detection, ResNet-based classifiers for threat discrimination, learned appearance features for re-identification
• Build hybrid perception pipelines: neural network detections → classical tracking → coordinate transformations → angle-only measurements for navigation
• Develop image processing chains: hot pixel filtering, adaptive thresholding, centroiding, connected component analysis, star catalog matching
• Deploy models to edge hardware: quantize neural networks (INT8), integrate with C++ inference engines (ONNX Runtime, TensorRT), optimize for space-qualified processors
• Implement coordinate transformations: pixel → camera frame → body frame → Earth-Centered Inertial (ECI), accounting for lens distortion and attitude uncertainty
• Generate synthetic training data: render spacecraft in Blender with domain randomization (lighting, attitudes, backgrounds), create labeled datasets for rare scenarios
• Validate end-to-end performance: software-in-the-loop simulation, processor-in-the-loop testing, hardware-in-the-loop with real camera feeds