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Applied AI Engineer - Flywheel Automation & Continuous Learning

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Kodiak Robotics

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Location:
United States , Mountain View

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Contract Type:
Not provided

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Salary:

180000.00 - 240000.00 USD / Year

Job Description:

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.

Job Responsibility:

  • 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:

  • 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 through Kaiser Permanente, Anthem, and Guardian (including a medical plan with infertility benefits)
  • Flexible PTO 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, One Medical, Gympass, Spring Health
  • Fidelity 401(k)
  • Commuter, FSA, Dependent Care FSA, HSA
  • Various incentive programs (referral bonuses, patent bonuses, etc.)

Additional Information:

Job Posted:
December 09, 2025

Employment Type:
Fulltime
Work Type:
On-site work
Job Link Share:

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