Job Description:

We are looking for a Machine Learning / AI Engineer (Part-Time) to design, train, and optimize the perception models that power ROZOR robots.
In this role, you will work with real-world robotics data to build algorithms that enhance environmental awareness—such as object detection, semantic segmentation, behavior prediction, and multi-modal fusion.

Your work will directly impact how ROZOR robots understand people, obstacles, and dynamic spaces as they operate in hospitals, malls, warehouses, and commercial buildings.

Responsibilities:

Train and optimize deep learning models for:

• Object detection, tracking, and classification
• Semantic segmentation and mapping
• Behavior and motion prediction
• Scene understanding in dynamic indoor environments
• Build data pipelines for dataset creation, annotation, preprocessing, and evaluation
• Work with multi-modal sensor data (RGB, depth, LiDAR, radar)
• Integrate ML models into perception and autonomy stacks on ROZOR robots
• Optimize inference performance on embedded compute (Jetson, ARM, GPU)
• Validate model performance through real-world robot testing
• Collaborate with perception, autonomy, and embedded teams to deploy production-ready ML systems

Preferred Qualifications:

• Bachelor’s/Master’s degree (or current student) in Computer Science, AI, Robotics, or related field
• Strong foundation in machine learning and deep learning
• Proficiency in Python, PyTorch or TensorFlow
• Experience training models in detection, segmentation, tracking, or classification
• Hands-on experience with image or point-cloud datasets
• Familiarity with OpenCV, NumPy, and ML tooling
• Strong debugging and experiment evaluation skills
• Ability to work independently in a fast-moving robotics environment