Applied Ai Engineer - Flywheel Automation & Continuous Learning

Kodiak Robotics

Mountain View, CA, United States
Base: $180,000 - $240,000 usd; bonus/equity: compe...
On-site
3+ years production ml infrastructure experience
Deep proficiency in python and pytorch
Experience with distributed training frameworks like ray or horovod
Kodiak Robotics is seeking an Applied AI Engineer to design the end-to-end AI Flywheel that powers continuous learning across their fleet of autonomous trucks

Job Summary

  • Kodiak Robotics is seeking an Applied AI Engineer to design the end-to-end AI Flywheel that powers continuous learning across their fleet of autonomous trucks.
  • The role involves building multi-node distributed training pipelines and developing smart data mining strategies to prioritize valuable training data from massive logs.
  • Candidates will benefit from competitive compensation including equity, comprehensive health plans, flexible PTO, and office perks like free catered lunches and EV charging.

Matching Summary

Kodiak Robotics is seeking an Applied AI Engineer to design the end-to-end AI Flywheel that powers continuous learning across their fleet of autonomous trucks.

Salary

Base: $180,000 - $240,000 USD; Bonus/Equity: Competitive equity and annual bonuses included; Benefits: Medical, Dental, Vision, 401(k), and wellness programs

Skills & Requirements

Must-have

  • 3+ years production ML infrastructure experience
  • Deep proficiency in Python and PyTorch
  • Experience with distributed training frameworks like Ray or Horovod
  • Pipeline orchestration tools such as Airflow or Kubeflow
  • Ability to scale systems for petabyte-scale data

Nice-to-have

  • Experience in autonomous vehicles or robotics
  • Prior work with self-supervised or active learning
  • Familiarity with Docker and model packaging workflows
  • Comfort working in cross-functional research teams
  • Mindset of ownership and systematic improvement

Key Requirements

  • Bachelor's, Master's, or PhD in Computer Science or related field
  • 3+ years of experience building production-grade ML pipelines
  • Strong engineering fundamentals and debugging skills

Work Rights

Not specified

Tailored Resume

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