Applied Ai Engineer Flywheel Automation Continuous Learning

## About the role 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. ## Responsibilities 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. ## 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 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 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 - Our office is centrally located in Mountain View, CA - 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.)