<div class="content-intro"><p>Kodiak AI, Inc. (Nasdaq: KDK), founded in 2018, is a leader in Physical AI, developing driverless technology that powers machines that move. Its Kodiak Driver is a vehicle-agnostic autonomous driving system that combines AI-powered software with modular hardware. Today it operates in long-haul trucking, industrial trucking, and defense. In 2024, Kodiak launched commercial Driver-as-a-Service operations with no one in the cab, and plans to launch driverless long-haul service between Dallas and Houston by the end of 2026.<br><br>Kodiak has partnered with many of the biggest names in freight, including Bosch for scaled hardware production, AWS, and leading customers including Atlas Energy Solutions, IKEA, Bridgestone, Werner Enterprises, C.R. England, Roehl Transport, and General Dynamics Land Systems.</p></div><div> <p><span style="font-family: helvetica, arial, sans-serif; font-size: 12pt;">Kodiak is seeking Staff Machine Learning Engineers, focusing on model deployment to help build the intelligence that powers the Kodiak Driver. Our ML teams work across perception, prediction, planning, and AI infrastructure to turn real-world driving data into models that enable safe and scalable autonomous trucking.</span></p> <p><span style="font-family: helvetica, arial, sans-serif; font-size: 12pt;">In this role, you will design and deploy machine learning systems that improve our vehicles’ ability to understand the world, predict the behavior of other road users, and make safe driving decisions. You will collaborate closely with robotics, autonomy, and infrastructure teams to continuously improve the performance of our autonomy stack using large-scale data from our growing fleet.</span></p> <span style="font-family: helvetica, arial, sans-serif; font-size: 12pt;">This is a high-impact opportunity to work on cutting-edge AI systems operating in the real world, where every mile driven improves our models and brings autonomous trucking closer to global deployment.</span><br><br><span style="font-size: 12pt; font-family: helvetica, arial, sans-serif;"><strong>In this role, you will:</strong></span></div> <ul data-list-tree="true" data-indent="0" data-border="0"> <li style="font-family: helvetica, arial, sans-serif; font-size: 12pt;"><span style="font-family: helvetica, arial, sans-serif; font-size: 12pt;">Help design, train, with a focus towards deploying onboard machine learning models that improve the performance/latency of the Kodiak autonomy stack which includes quantization, pruning, converting to ONNX/TensorRT, custom GPU kernels and profiling.</span></li> <li style="font-family: helvetica, arial, sans-serif; font-size: 12pt;"><span style="font-family: helvetica, arial, sans-serif; font-size: 12pt;">Help identify and achieve parity between onboard and deployed offboard models using validation on HIL </span></li> <li style="font-family: helvetica, arial, sans-serif; font-size: 12pt;"><span style="font-family: helvetica, arial, sans-serif; font-size: 12pt;">Collaborate with cross-functional teams including perception, planning, simulation, and autonomy infrastructure to integrate ML models into production systems.</span></li> <li style="font-family: helvetica, arial, sans-serif; font-size: 12pt;"><span style="font-family: helvetica, arial, sans-serif; font-size: 12pt;">Analyze real-world driving logs to identify edge cases and improve model robustness and safety.</span></li> <li style="font-family: helvetica, arial, sans-serif; font-size: 12pt;"><span style="font-family: helvetica, arial, sans-serif; font-size: 12pt;">Use profiling tooling to additionally help improve the train time for models by identifying and removing bottlenecks.</span></li> <li style="font-family: helvetica, arial, sans-serif; font-size: 12pt;"><span style="font-family: helvetica, arial, sans-serif; font-size: 12pt;">Contribute to the development of scalable AI infrastructure that supports continuous learning and deployment across Kodiak’s fleet.</span></li> </ul> <div><span style="font-size: 12pt; font-family: helvetica, arial, sans-serif;"><strong>What you’ll bring:</strong></span></div> <ul data-list-tree="true" data-indent="0" data-border="0"> <li style="font-family: helvetica, arial, sans-serif; font-size: 12pt;"><span style="font-family: helvetica, arial, sans-serif; font-size: 12pt;">MS or PhD in Computer Science, Robotics, Machine Learning, or a related technical field, or equivalent practical experience.</span></li> <li style="font-family: helvetica, arial, sans-serif; font-size: 12pt;"><span style="font-family: helvetica, arial, sans-serif; font-size: 12pt;">6+ years experience deploying machine learning or deep learning systems in production environments.</span></li> <li style="font-family: helvetica, arial, sans-serif; font-size: 12pt;"><span style="font-family: helvetica, arial, sans-serif; font-size: 12pt;">Proficiency in Python, C++ and modern ML frameworks such as PyTorch or TensorFlow.</span></li> <li style="font-family: helvetica, arial, sans-serif; font-size: 12pt;"><span style="font-family: helvetica, arial, sans-serif; font-size: 12pt;">Experience working with large-scale distributed training systems.</span></li> <li style="font-family: helvetica, arial, sans-serif; font-size: 12pt;"><span style="font-family: helvetica, arial, sans-serif; font-size: 12pt;">Solid understanding of optimization, and machine learning fundamentals.</span></li> <li style="font-family: helvetica, arial, sans-serif; font-size: 12pt;">&l