← Serch more jobs

Applied AI Engineer - Flywheel Automation & Continuous Learning

LinkedIn Kodiak San Francisco, CA
Mid-Senior level Posted March 14, 2026 Job link
Thinking about this job
Not Met Priorities
What still needs stronger evidence
Requirements
  • 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.
  • Familiarity with containerization (Docker), model packaging, and deployment workflows.
Preferred Skills
  • 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.
Education
  • (Not required) – Bachelor’s, Master’s, or PhD in Computer Science, Machine Learning, Robotics, or a related field.