Lodestar Space
Software Engineer: On-board Autonomy
Los Angeles, US · Senior · Full-time
Work authorization required$120k-$145kDetected 35 days ago
PythonC++AlgorithmsGitAWSGCPAzureCI/CDLinuxMachine LearningTensorFlowPyTorchRoboticsControlsResearchCommunication
About the role
- These models adapt dynamically to changing conditions, enabling real-time autonomous decision-making even in communications-limited or uncertain environments.
- We proudly have an "extreme ownership" oriented engineering culture.
- 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.
Responsibilities
- Design and implement on-board decision-making models that recommend and adapt strategies in real time
- Develop autonomous decision algorithms that integrate information from perception, state estimation, and intent prediction models to execute mission objectives
- Research and implement ML models for decision making - everything from lit. review, through training, to deployment
- Implement decision models that adapt dynamically to changing mission context, environmental conditions, and system status
- Develop frameworks for continuous re-evaluation of active strategies to ensure resilient and adaptive behavior under uncertainty
- Support real-time autonomy in communications-limited or time-critical scenarios
- Build and maintain autonomy infrastructure, testing frameworks, and deployment pipelines for space missions
Requirements
- 2+ years of distinguished industry experience in autonomy, decision-making, or control systems for aerospace/robotics
- Strong proficiency in C++ and Python and DL frameworks (PyTorch, TensorFlow)
- Track record implementing autonomy applications in real-time or safety-critical environments
- Experience with distributed training and cloud-based scaling of ML models (AWS, GCP, or Azure)
- Experience with Linux, Git, and CI/CD pipelines
- Strong understanding of distributed autonomy, networking, and communication protocols
Nice to have
- Preferred Skills & Experience
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.
- (E1) Junior Software Engineer: $120,000 - $145,000 / year
- (E2) Software Engineer: $140,000 - $180,000 / year
- (E3) Senior Software Engineer: Competitive
Benefits
- 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
- Bachelor's or Master's degree in Computer Science, Machine Learning, Robotics, a related field, or equivalent experience
- Demonstrated experience with machine learning applied to decision-making or control problems
- Track record with optimal control, planning, or reinforcement learning in real-time systems
Visa & Work Authorization
- citizen, lawful permanent resident of the U
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This listing is sourced directly from Lodestar Space's careers page and normalized into a canonical job model.