About the role
<div class="content-intro"><p>Kodiak Robotics, Inc. was founded in 2018 and has become a leader in autonomous ground transportation committed to a safer and more efficient future for all. The company has developed an artificial intelligence (AI) powered technology stack purpose-built for commercial trucking and the public sector. The company delivers freight daily for its customers across the southern United States using its autonomous technology. In 2024, Kodiak became the first known company to publicly announce delivering a driverless semi-truck to a customer. Kodiak is also leveraging its commercial self-driving software to develop, test and deploy autonomous capabilities for the U.S. Department of Defense.</p></div><div class="section page-centered"> <div> <p><span style="font-size: 12pt;">Kodiak is seeking a world-class Applied AI Engineer to design and build the AI Flywheel - the closed-loop system that powers continuous learning across our fleet of autonomous trucks.</span></p> <p><span style="font-size: 12pt;">In this role, you will own the architecture and automation of a complete data-to-model flywheel: from mining hard edge cases, to orchestrating distributed training pipelines, to deploying models across our large-scale AI infrastructure. Your work will ensure that our models improve rapidly and continuously with every mile driven.</span></p> <span style="font-size: 12pt;">This is a high-impact, cross-functional role where you’ll interface with our perception, foundation model, and infrastructure teams to transform real-world driving data into smarter models and safer autonomy.</span></div> </div> <div class="section page-centered" data-qa="preview-list-item-0"> <h3 data-qa="preview-list-item-0-text"><span style="font-family: helvetica, arial, sans-serif; font-size: 12pt;">In this role, you will:</span></h3> <ul> <li style="font-size: 12pt;"><span style="font-size: 12pt;">Design and implement the end-to-end AI Flywheel, platforms for training, validation, deployment, and building a robust automated system.</span></li> <li style="font-size: 12pt;"><span style="font-size: 12pt;">Build and maintain multi-node distributed training pipelines using tools like PyTorch DDP, Horovod, or Ray.</span></li> <li style="font-size: 12pt;"><span style="font-size: 12pt;">Develop smart data mining and active learning strategies to prioritize valuable training data from petabyte-scale logs.</span></li> <li style="font-size: 12pt;"><span style="font-size: 12pt;">Automate model evaluation and selection pipelines to support rapid iteration and closed-loop deployment