Applied AI Engineer - Flywheel Automation & Continuous Learning

Applied AI Engineer - Flywheel Automation & Continuous Learning 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 full job description covers all associated skills, previous experience, and any qualifications that applicants are expected to have. 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. 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. 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. In this role, you will:

Design and implement the end-to-end AI Flywheel, platforms for training, validation, deployment, and building a robust automated system. Build and maintain multi-node distributed training pipelines using tools like PyTorch DDP, Horovod, or Ray. Develop smart data mining and active learning strategies to prioritize valuable training data from petabyte-scale logs. Automate model evaluation and selection pipelines to support rapid iteration and closed-loop deployment. Build infrastructure for seamless model image packaging, validation, and rollout across Kodiak’s autonomous fleet and AI platform. Ensure that the flywheel is reliable, reproducible, and scalable, capable of learning from millions of real-world miles. What you'll bring:

Bachelor’s, Master’s, or PhD in Computer Science, Machine Learning, Robotics, or a related field. 3+ years of experience building production-grade ML infrastructure or model pipelines. Deep proficiency in Python and deep learning frameworks (e.g., PyTorch, TensorFlow). Experience with distributed training and pipeline orchestration (e.g., Airflow, Kubeflow, Dagster). Strong engineering fundamentals, debugging skills, and ability to scale systems. Passion for turning real-world data into self-improving AI systems. Ideal candidate will also bring: Experience in autonomous vehicles, robotics, or other sensor-rich real-world ML systems. Prior work with self-supervised learning, active learning, or large-scale data curation. Familiarity with containerization (Docker), model packaging, and deployment workflows. Comfort working in cross-functional teams with research scientists, infra engineers, and robotics experts. A mindset of ownership, experimentation, and systematic improvement. What we offer: Competitive compensation package including equity and biannual bonuses Excellent Medical, Dental, and Vision plans Flexible PTO and generous parental leave policies Office perks: dog-friendly, free catered lunch, a fully stocked kitchen, and free EV charging Fidelity 401(k) Commuter, FSA, Dependent Care FSA, HSA Kodiak is committed to equal opportunity employment regardless of race, ethnicity, religion, gender identity, sexual orientation, age, disability, or veteran status, or any other basis protected by applicable law.

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