Software Engineer (Perception)
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Summary
As a Software Engineer - Perception at Lodestar, you’ll research and build computer vision and ML algorithms to detect, classify, and track space targets in real time, developing models and infrastructure for autonomous decision-making in space environments using C++, Python, and GPU-accelerated tools.
- As a Software Engineer - Perception at Lodestar you’ll be joining the perception and machine visions teams to rapidly grow our vision and perception models at MITHRIL’s center
- You’ll focus on researching and building algorithms to detect, classify and understand unknown space targets in real-time
- By combining computer vision, image processing and machine learning, you’ll develop custom models - providing the foundation for autonomous decision-making in complex and uncertain space environments
- Scoping architecture for the perception system core to Lodestar’s autonomy software suite
- Research and adapt novel perception algorithms - everything from lit. review, through training and evaluation, to optimisation and deployment
- Design, develop ML algorithms from the ground up, in addition to build on and optimizing our existing models for edge computing
- Further develop our robust methods for predicting relative pose of dynamic space targets in harsh and unpredictable visual environments
- Integrate perception models into mission simulation environments and real-time autonomy pipelines
- Contribute to the design of realistic sensor models and digital twins to improve perception fidelity in mission scenarios
- Own perception tooling, model training infrastructure, and evaluation frameworks for ongoing development and deployment
- Collaborate across autonomy, estimation, and mission software teams to ensure perception fidelity, performance, and scalability
- Experience developing and deploying ML models to real-time systems
- 2+ years of distinguished industry experience in Machine Learning, robotics, computer vision, or a related field
- Excellent software engineering skills in C++ and Python
- Broad understanding of modern perception systems and their architecture
- Bachelor’s or Master’s degree in, AI/ML, Computer Science, Robotics, a related field, or equivalent experience
- Strong DNN/ML background and experience in CV and image processing libraries (OpenCV, CUDA-accelerated vision, PCL)
- Strong understanding of networking and communication protocols for distributed autonomy systems
- Comfortable with containerization tools such as Docker and Kubernetes
- Experience with Linux, Git, and CI/CD pipelines
- Experience with distributed training and cloud-based scaling of ML models (AWS, GCP, or Azure)
- Track record optimizing neural networks and geometric algorithms using CUDA kernels, TensorRT, or other GPU acceleration frameworks
- Familiarity with image processing techniques (e.g., feature extraction, segmentation, filtering, stereo matching) to support 3D reconstruction and target classification
- Experience processing sensor measurements from a variety of sensors including RADAR, electro-optical sensors, RF sensors, or LIDAR