<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 the critical hardware & software necessary 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>as a single platform, we deliver a fully autonomous end-to-end protection spacecraft service.</p> <hr> <h3><strong>About the Job</strong></h3> <p>As a<span class="Apple-converted-space"> <strong>Software Engineer I - Perception</strong></span><span class="Apple-converted-space"> </span>at Lodestar, you’ll be joining the perception and machine vision teams to rapidly grow our vision and perception models at<span class="Apple-converted-space"> </span><em>MITHRIL’s</em><span class="Apple-converted-space"> </span>center. </p> <p>You'll help build and refine algorithms that detect, classify and understand unknown space targets in real time. Working alongside senior perception engineers, you'll combine computer vision, image processing and machine learning to develop the custom models that underpin autonomous decision-making in complex and uncertain space environments.</p> <p>This is an early-career role. We're looking for strong fundamentals and fast learning rather than a long track record, and you'll be given real ownership early with the support to grow into it.</p> <p>We proudly have an "extreme ownership" oriented engineering culture.</p> <hr> <h3><strong>What You’ll Do</strong></h3> <ul> <li>Contribute to the perception system at the core of Lodestar's autonomy software suite</li> <li>Work through the full lifecycle of perception algorithms alongside senior engineers including literature review, training, evaluation, optimisation and deployment</li> <li>Build on and optimise our existing models for edge computing, and develop new components with guidance from the perception leads</li> <li>Help develop and test our methods for predicting the relative pose of dynamic space targets in harsh and unpredictable visual environments</li> <li>Integrate perception models into mission simulation environments and real-time autonomy pipelines</li> <li>Contribute to the design of realistic sensor models and digital twins to improve perception fidelity in mission scenarios</li> <li>Maintain and extend our perception tooling, model training infrastructure, and evaluation frameworks</li> <li>Collaborate across the autonomy, estimation, and mission software teams to support perception fidelity, performance, and scalability</li> </ul> <p> </p> <hr> <h3><strong>Basic Qualifications</strong></h3> <ul> <li>Bachelor's or Master's degree in AI/ML, Computer Science, Robotics, a related field, or equivalent experience</li> <li>0–2 years of professional experience in machine learning, robotics, computer vision, or a related field. Internships, research placements, and substantial academic or personal projects all count</li> <li>Solid software engineering skills in Python, and working proficiency in C++</li> <li>Foundational DNN/ML knowledge and hands-on experience with computer vision or image processing libraries (e.g. OpenCV)</li> <li>Demonstrated ability to take an ML model from training through to evaluation, in any setting — coursework, research, or industry</li> </ul> <hr> <h3><strong>Preferred Skills & Experience</strong></h3> <ul> <li>Experience developing or deploying ML models to real-time or resource-constrained systems</li> <li>Broad understanding of modern perception systems and their architecture</li> <li>Exposure to sensor measurements from RADAR, electro-optical sensors, RF sensors, or LIDAR</li> <li>Familiarity with image processing techniques (e.g. feature extraction, segmentation, filtering, stereo matching) to support 3D reconstruction and target classification</li> <li>Experience optimising neural networks or geometric algorithms using CUDA kernels, TensorRT, or other GPU acceleration frameworks</li> <li>Exposure to distributed training or cloud-based scaling of ML models (AWS, GCP, or Azure)</li> <li>Experience with Linux, Git, and CI/CD pipelines</li> <li>Comfortable with containerisation tools such as Docker and Kubernetes</li> <li>Understanding of networking and communication protocols for distributed autonomy systems</li> </ul> <p> </p> <hr> <h3>ITAR Requirements</h3> <p><em>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<span class="Apple-converted-space"> </span><a href="https://www.pmddtc.state.gov/?id=ddtc_kb_article_page&sys_id=24d528fddbfc930044f9ff621f961987">here&