Software Engineer - State Estimation & Prediction (III)

• 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
• Collaborate with cross-functional teams, including perception and on-board autonomy, to ensure prediction fidelity, robustness, and scalability across missions

Software Engineering, Artificial Intelligence (AI), Algorithms, Predictive Modeling, Research & Development (R&D), Machine Learning, Software Engineering, Benchmarking, Forecasting, Simulation, * 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)
• Familiarity with trajectory modelling, multi-body dynamics, or orbital mechanics
• Demonstrated ability to work through open-ended technical problems and communicate your reasoning clearly, * 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
• Experience applying sequence-to-sequence models to forecasting problems in dynamic environments
• 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
• Experience with Linux, Git, and CI/CD pipelines
• Familiarity with containerisation tools such as Docker and Kubernetes
• Awareness of real-time systems, multi-threading, and performance optimisation
• Understanding of networking and communication protocols for distributed autonomy systems
• Contributions to open-source projects, or participation in student rocketry, CubeSat, robotics, or autonomous vehicle teams

• (P2) Developing: $115,000 - $174,000 / year
• (P3) Career: $136,000 - $200,000 / year
• Meaningful equity incentives as part of our employee option pool
• Flexible PTO with generous paid vacation, holidays, and sick leave
• Comprehensive medical, dental & vision coverage
• 401(k) retirement plan with company match
• Based in Los Angeles, Compensation bands are determined by role, level, location, and alignment with market data. Individual level and base pay is determined on a case-by-case basis and may vary based on job-related skills, education, experience, technical capabilities and internal equity. In addition to base salary, for full-time hires, you may also be eligible for long-term incentives, in the form of stock options , and access to medical, vision and dental coverage, as well as access to a 401(k) retirement plan.