Hiring: Software Engineer I or II: State Estimation & Prediction Company: Lodestar Space Location: El Segundo, CA Job Posted Time: 2026-09-10 10:32:32 Employment Type: Full-time Target Skills & Keywords : C++, CI/CD, Deep Learning, Docker, Git, Kubernetes, Linux, Machine Learning, PyTorch, Python, TensorFlow, TensorRT, Transformers About the job Experience: •Internship, industrial placement, or research assistantship in aerospace, robotics, estimation, or a related field •A dissertation, thesis, or capstone project in state estimation, sensor fusion, or trajectory forecasting •Operational familiarity with sensor fusion techniques (e.g. combining radar, optical, and inertial data) •Exposure to GPU acceleration (CUDA, TensorRT) for neural network training and inference •Operational familiarity with containerisation tools such as Docker and Kubernetes Required Skills: •Contribute to the design and implementation of Lodestar's core state estimation and prediction architecture for autonomous spacecraft operations •Support research into novel estimation and prediction algorithms, from literature review through training and tuning to optimisation and deployment •Implement, test, and benchmark classical and neural estimators that track the current state and trajectory of multiple dynamic targets in real time •Build and evaluate neural models that forecast future trajectories and behavioural patterns of targets •Assist in the development of intent inference models that identify actions and dynamically rank threat levels •Integrate state estimation and prediction models into mission simulation environments and autonomy decision systems •Partner cross-functionally with cross-functional teams, including perception and on-board autonomy, to ensure prediction fidelity, robustness, and scalability across missions Qualifications: •Bachelor's, Master's, or PhD in Computer Science, Aerospace, Robotics, Applied Mathematics, or a related field, completed within the last 24 months or due to be completed before your start date •Working proficiency in C++ and Python, evidenced through coursework, research, internships, or personal projects •Grounding in probabilistic state estimation (Kalman filters, particle filters, Bayesian inference), whether from taught modules, research, or self-directed work •Practical exposure to a deep learning framework (PyTorch, TensorFlow), including sequence modelling (seq2seq, RNNs, LSTMs, Transformers) •Operational familiarity with trajectory modelling, multi-body dynamics, or orbital mechanics •Demonstrated ability to work through open-ended technical problems and communicate your reasoning clearly Compensation: •$99,000 - $133,000 / year •Meaningful equity incentives as part of our employee option pool Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don't miss this opportunity to join a forward-thinking team!