Advance core computer vision model performance (object detection, segmentation, OCR) for warehouse inventory scanning across drone and MHE Vision platforms
Own the full ML lifecycle from research and experiment design through production deployment and monitoring — applying rigorous ablation studies and SOTA methodology
Collaborate with the ML infrastructure team on model optimization and deployment across cloud and edge inference targets (ONNX, TensorRT, quantization)
Work with Operations and Product to understand customer needs and translate them into ML improvements with measurable business impact
Provide technical leadership and mentorship to the ML team, raising standards for experiment design, model evaluation, and production readiness
Explore next-generation perception capabilities, including embedded and on-prem inference optimization for new deployment targets

10+ years of experience in machine learning or computer vision
Deep expertise in CNNs, object detection, image segmentation, and OCR using PyTorch (preferred) or TensorFlow
Strong Python proficiency and software engineering fundamentals; hands-on experience with OpenCV and GPU computing
Track record of delivering production ML systems at scale, including model training, evaluation, and deployment
MS or PhD in Computer Science, Machine Learning, Robotics, or a related field

Principal Machine Learning Scientist

Key skills