Imitation Learning Engineer

ko-br is building Physical AI for warehouses, solving complex tasks like palletizing, kitting, and pick-and-pack operations. We are looking for an Imitation Learning Engineer to join our team and develop algorithms that allow our AI systems to learn from human demonstrations.

About ko-br:
ko-br builds Physical AI for warehouses—solving palletizing, kitting, and pick-and-pack tasks that giants like Amazon/ABB/Universal Robots haven't cracked. Our tech lets cobots adapt to mixed SKUs, grip slips, and chaotic environments in real time without reconfiguration or coding. We believe in Data Dignity, where humans are respected and compensated for teaching machines, sharing in the value their knowledge creates.

Responsibilities:
- Design and implement imitation learning algorithms for robotic tasks
- Collect and label data for training imitation learning models
- Collaborate with the backend team to deploy these models in our products
- Research and implement novel imitation learning techniques
- Optimize models for real-time performance and accuracy

Requirements:
- Strong background in machine learning and imitation learning
- Experience with reinforcement learning and behavioral cloning
- Familiarity with robotics and cobot integration
- Programming skills in Python, Java, or similar languages
- Understanding of neural networks and deep learning
- Experience with data processing and analysis

Why join ko-br?
- Work with state-of-the-art AI and real cobots (UR, ABB, KUKA)
- Build tech that solves valuable problems—today
- Competitive salary with equity opportunities
- Remote-first culture with flexible schedules
- Opportunities for professional growth and learning
- Collaborative team with diverse backgrounds and expertise