Software Engineer II: On-board Autonomy

PassFort; Los Angeles (CA); On-site; USD 115,000 - 200,000; Full time

Benefits offered by this job

Equity incentives

Flexible PTO

Medical, dental & vision coverage

401(k) retirement plan

LA location

Job summary

Lodestar is hiring a Software Engineer II - On-board Autonomy to develop decision-making systems for autonomous spacecraft. You will design models that reason about context, capabilities, and environment to select actions in real time.

The role emphasizes end-to-end ML workflows from research to deployment in space-grade environments. You will work in a culture centered on extreme ownership, tackling perception-to-action pipelines and ensuring resilient autonomous behavior across challenging

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Robotics, or related field.
• 2+ years of industry experience in autonomy, decision-making, or control for aerospace/robotics.
• Strong proficiency in C++ and Python and DL frameworks (PyTorch, TensorFlow).
• Demonstrated experience applying ML to decision-making or control tasks.
• Experience with real-time systems, planning, or reinforcement learning.

Responsibilities

• Design and implement on-board decision-making models for real-time autonomy.
• Integrate perception, state estimation, and intent prediction for mission objectives.
• Research and deploy ML models from literature through training to deployment.
• Develop adaptive decision models for changing mission contexts.
• Build testing frameworks and deployment pipelines for space missions.
• Support autonomy in communications-limited or time-critical scenarios.

Skills

C++ proficiency

Python proficiency

Machine learning for autonomy

Real-time systems

Multi-agent decision-making

Education

Bachelor's or Master's in CS/ML/Robotics

Tools

PyTorch

TensorFlow

Linux

Git

Docker

Kubernetes

CI/CD

Job description

About Lodestar

Lodestar's mission is to develop the first "Protect and Defend" capability for high-value space assets in orbit. Our flagship product,MITHRIL, is our hardware-agnostic, AI-enabled autonomy software suite that enables us to augment any off-the-shelf spacecraft with the ability to autonomously detect, characterise, and reversibly neutralise orbital threats. By building on the proven space heritage of our best-in-class satellite-bus partners and fully integratingMITHRILinto single unified platform, we deliver an end-to-end, autonomous in-space superiority service.

About the Job

At Lodestar, as aSoftware Engineer II - On-board Autonomy, you’ll be developing the decision-making systems at the heart of Lodestar’s autonomy suite. You’ll focus on creating algorithms that evaluate mission context, system capabilities, and environmental conditions to recommend and execute optimal actions. These models adapt dynamically to changing conditions, enabling real-time autonomous decision-making even in communications-limited or uncertain environments. Your work will bridge perception, prediction, and control, allowing spacecraft to operate intelligently, efficiently, and resiliently across complex mission scenarios.

We proudly have an "extreme ownership" oriented engineering culture.

What You’ll Do

• 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

Basic Qualifications

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Robotics, a related field, or equivalent experience
• 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)
• 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
• Familiarity with multi-agent decision-making or planning under uncertainty

Preferred Skills & Experience

• Track record implementing autonomy applications in real-time or safety-critical environments
• Experience integrating perception and prediction outputs into decision frameworks
• Familiarity with resource-aware strategy selection and optimization under uncertainty
• Background in reinforcement learning, hierarchical planning, or adaptive control
• Experience with distributed training and cloud-based scaling of ML models (AWS, GCP, or Azure)
• Experience with Linux, Git, and CI/CD pipelines
• Comfortable with containerization tools such as Docker and Kubernetes
• Familiarity with real-time systems, multi-threading, and performance optimization
• Strong understanding of distributed autonomy, networking, and communication protocols

ITAR Requirements

To conform to U.S. Government space technology export regulations, including the International Traffic in Arms Regulations (ITAR) you must be a U.S. citizen, lawful permanent resident of the U.S., protected individual as defined by 8 U.S.C. 1324b(a)(3), or eligible to obtain the required authorizations from the U.S. Department of State. Learn more about the ITAR.

Compensation & Benefits

• Pay Range:
  • (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
• LA

Additional Information

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 theform of stock options, and access tomedical, vision and dental coverage, as well asaccess to a 401(k) retirement plan.

Lodestar is an Equal Opportunity Employer; employment with Lodestar is governed on the basis of merit, competence and qualifications and will not be influenced in any manner by race, color, religion, gender, national origin/ethnicity, veteran status, disability status, age, sexual orientation, gender identity, marital status, mental or physical disability or any other legally protected status.