Lodestar is building the first autonomous AI fighter-pilot for space, to power in-orbit bodyguard satellites and deliver orbital defence as a service to high-value assets. Backed by Entrepreneur First.
About the role
At Lodestar, as a Software 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.
What they're looking for
- 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
More about this role
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 integrating MITHRIL into single unified platform, we deliver an end-to-end, autonomous in-space superiority service.
At Lodestar, as a Software 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...
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