Autonomy Engineer: State Estimation & Trajectory Prediction (I/II)

Lodestar; Los Angeles (CA); On-site; USD 99,000 - 174,000; Full time

Benefits offered by this job

Equity incentives

Flexible PTO

401(k) retirement plan with company-

Medical, vision & dental coverage

Job summary

Lodestar seeks a Graduate Software Engineer (I or II) to lead the development of state estimation and prediction models at the core of its MITHRIL autonomy suite. You will research and develop probabilistic estimation fused with machine learning to track targets, predict trajectories, and assess intent.

Our extreme ownership culture emphasizes hands-on design, rigorous testing, and collaboration with cross-functional teams to ensure robust, scalable autonomy across missions.

Qualifications

• Bachelor’s, Master’s, or PhD in Computer Science, Aerospace, Robotics, Applied Mathematics, or related field, completed within last 24 months or before start date
• Proficiency in C++ and Python demonstrated via coursework, research, internships, or projects
• Grounding in probabilistic state estimation (Kalman filters, particle filters, Bayesian inference)
• Experience with deep learning frameworks (PyTorch, TensorFlow) including sequence models (seq2seq, RNNs, LSTMs, Transformers)
• Familiarity with trajectory modelling, multi-body dynamics, or orbital mechanics
• Ability to tackle open-ended technical problems and communicate reasoning clearly

Responsibilities

• Contribute to core state estimation and prediction architecture for autonomous spacecraft operations
• Research novel estimation and prediction algorithms from literature through training and deployment
• Implement, test, and benchmark classical and neural estimators tracking targets in real time
• Build and evaluate neural models forecasting trajectories and behavioral patterns
• Assist in development of intent inference models to identify actions and rank threat levels
• Integrate models into mission simulation environments and autonomy decision systems
• Collaborate with perception and on-board autonomy teams to ensure fidelity, robustness, and scalability

Skills

C++

Python

Probabilistic state estimation

Deep learning

Education

Bachelor’s degree or higher in CS/related field

Tools

Linux

Git

Docker

Kubernetes

PyTorch

TensorFlow

Job description

Lodestar seeks a Graduate Software Engineer (I or II) to lead the development of state estimation and prediction models at the core of its MITHRIL autonomy suite. You will research and develop probabilistic estimation fused with machine learning to track targets, predict trajectories, and assess intent.

Our extreme ownership culture emphasizes hands-on design, rigorous testing, and collaboration with cross-functional teams to ensure robust, scalable autonomy across missions.