Software Engineer: On-board Autonomy

<h3>About Lodestar</h3> <p>Lodestar's mission is to develop the first "Protect and Defend" capability for high-value space assets in orbit. Our flagship product,<span class="Apple-converted-space"> </span><em>MITHRIL,</em><span class="Apple-converted-space"> </span>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 integrating<span class="Apple-converted-space"> </span><em>MITHRIL</em><span class="Apple-converted-space"> </span>into single unified platform, we deliver an end-to-end, autonomous in-space superiority service.</p> <h3><strong>About the Job</strong></h3> <p>At Lodestar, as a<span class="Apple-converted-space"> </span><strong>Software Engineer - On-board Autonomy</strong>, 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.</p> <p>We proudly have an "extreme ownership" oriented engineering culture. </p> <hr> <h3><strong>What You’ll Do</strong></h3> <ul> <li>Design and implement on-board decision-making models that recommend and adapt strategies in real time</li> <li>Develop autonomous decision algorithms that integrate information from perception, state estimation, and intent prediction models to execute mission objectives</li> <li>Research and implement ML models for decision making - everything from lit. review, through training, to deployment</li> <li>Implement decision models that adapt dynamically to changing mission context, environmental conditions, and system status</li> <li>Develop frameworks for continuous re-evaluation of active strategies to ensure resilient and adaptive behavior under uncertainty</li> <li>Support real-time autonomy in communications-limited or time-critical scenarios</li> <li>Build and maintain autonomy infrastructure, testing frameworks, and deployment pipelines for space missions</li> </ul> <hr> <h3><stron