Software Engineer; Perception, New Grad

• You’ll work on hybrid perception systems combining classical computer vision with modern deep learning for autonomous spacecraft: building multi-object tracking pipelines that fuse neural network detections with Kalman filtering, developing coordinate transformation chains from pixels to orbital frames, training models on synthetic space imagery, and deploying algorithms onboard under strict compute/power constraints
• Your work enables spacecraft to detect objects against star fields, track multiple targets through occlusions, discriminate threats from decoys, and generate angle measurements for navigation - using both classical geometric methods and learned representations where each approach excels
• This is entry-level work blending traditional robotics perception with modern ML
• You’ll implement Extended Kalman Filters, train neural networks in PyTorch, write C++ flight code, and see your algorithms operate in orbit
• This is a 3 month temporary employment engagement
• There is potential to convert to regular employment based on performance and business need
• 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, Res Net-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

• 100% Employer-Sponsored Healthcare:
  We've got you covered! Our comprehensive healthcare package is fully sponsored, ensuring you and your loved ones stay healthy and worry-free, so you can focus on shaping the future of space security.
• Generous Time Off:
  We believe in working hard and recharging fully. Our generous vacation policy gives you the flexibility to take the time you need to relax, explore, and come back energized to take on new challenges.
• Equity:
  Own an equity stake in True Anomaly as you build something transformative. With equity options, you're not just working for True Anomaly; you're an owner. As an essential part of our growth and future success, we want you to share in the upside potential!
• 401k and Roth 401k options:
  Plan for tomorrow with our 401K and Roth 401K options that put you in control of your financial future.
• Learning & Development Opportunities:
  Your growth fuels our innovation. We're committed to providing you with the resources and training to expand your skills, spark new ideas, and advance your career with us.

Strong debugging skills: tracking down lost tracks, numerical instability, and model failure modesU.S. Citizen (required for facility access and government contracts)
Coursework in both computer vision and estimation theory (or willingness to learn both)
Currently pursuing or recently completed Bachelor's or Master's degree in computer science, electrical engineering, robotics, aerospace engineering, or related technical field

Eagerness to learn the intersection of classical perception and modern MLProficiency in Python; some exposure to C++ (we'll teach you more)
Understanding of linear algebra, probability, and coordinate transformations

Ability to read research papers from both robotics (ICRA, IROS) and ML venues (CVPR,…