Kodiak Robotics, Inc. is a leader in autonomous ground transportation, developing AI-powered technology for commercial trucking and the public sector. They are committed to a safer and more efficient future, delivering freight daily using autonomous technology. Kodiak is also involved in deploying autonomous capabilities for the U.S. Department of Defense.

About the Position

Introduction

Kodiak Robotics, Inc., founded in 2018, is a leader in autonomous ground transportation, dedicated to creating a safer and more efficient future. The company builds AI-powered technology for commercial trucking and the public sector, delivering freight daily across the US with its autonomous technology. In 2024, Kodiak announced the first public delivery of a driverless semi-truck to a customer and also deploys its self-driving software for the U.S. Department of Defense.

Kodiak is seeking a world-class Applied AI Engineer to design and build the AI Flywheel, a closed-loop system for continuous learning across its fleet of autonomous trucks. In this high-impact, cross-functional role, you will own the architecture and automation of a complete data-to-model flywheel, ensuring rapid and continuous model improvement.

Responsibilities

Design and implement the end-to-end AI Flywheel, including 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.

Requirements

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.

Nice to Have

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, infrastructure engineers, and robotics experts.
A mindset of ownership, experimentation, and systematic improvement.

Benefits

Competitive compensation package including equity and annual bonuses.
Excellent Medical, Dental, and Vision plans through Kaiser Permanente, Cigna, and MetLife (including a medical plan with infertility benefits).
MetLife Legal Services, Identity & Fraud Protection, Hospital Indemnity Insurance, Accident Insurance, & Critical Illness Insurance.
Flexible PTO, 10 paid holidays, and generous parental leave policies.
Office perks: dog-friendly, free catered lunch, a fully stocked kitchen, and free EV charging.
Long Term Disability, Short Term Disability, Life Insurance.
Wellbeing Benefits - Headspace through Cigna, Calm through Kaiser, One Medical, Gympass, Spring Health through Cigna, Rula (mental health navigation).
Fidelity 401(k).
Commuter, FSA, Dependent Care FSA, HSA.
Various incentive programs (referral bonuses, patent bonuses, etc.).