About the TeamThis role work closely with a Senior Machine Learning Scientist and our Lead Machine Learning Infrastructure Engineer, alongside cross-functional partners in Cloud Engineering, Product, and Operations. The role spans both deep technical work and collaboration with teams closest to the customer. As a Principal-level IC, you'll have real input into technical direction - not just executing on decisions, but helping make them.
About the RoleWe are looking for a
Principal Machine Learning Scientist to advance the state of our computer vision systems for warehouse inventory scanning. You will work across the full ML lifecycle - from research and model architecture through training, deployment, and production monitoring - with a focus on delivering measurable improvements to detection, segmentation, and OCR accuracy across our drone and MHE Vision products.
This role is ideal for a senior ML practitioner who wants principal-level impact on a core product, a variety of deployment targets (cloud, on-prem, embedded), and real-world data with tangible business outcomes.
What You'll Do- 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
What You'll Need- 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
Nice to Have- Experience with drone, robotics, or autonomous systems perception
- Publications in top vision or robotics conferences (CVPR, ICCV, ICRA, NeurIPS, CoRL)
- Experience designing and deploying models for real-time inference on constrained compute platforms
- Warehouse, logistics, or supply chain domain experience
