Gather AI
Principal Machine Learning Scientist
Open to Remote (USA); Pittsburgh, PA · Principal
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About the role
- We are looking for a Principal Machine Learning Scientist to advance the state of our computer vision systems for warehouse inventory scanning.
- 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.
- The role spans both deep technical work and collaboration with teams closest to the customer.
Responsibilities
- 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)
- Provide technical leadership and mentorship to the ML team, raising standards for experiment design, model evaluation, and production readiness
Requirements
- 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
Nice to have
- Experience with drone, robotics, or autonomous systems perception
- Experience designing and deploying models for real-time inference on constrained compute platforms
- Warehouse, logistics, or supply chain domain experience
- Deep expertise in CNNs, object detection, image segmentation, and OCR using PyTorch (preferred) or TensorFlow
Benefits
- Advance core computer vision model performance (object detection, segmentation, OCR) for warehouse inventory scanning across drone and MHE Vision platforms
- 10+ years of experience in machine learning or computer vision
- MS or PhD in Computer Science, Machine Learning, Robotics, or a related field
Company info
- Are you ready to build the future of the supply chain? At Gather AI, we're not just creating software
- we're pioneering a new era of warehouse intelligence. We've developed a groundbreaking, vision-powered platform that uses autonomous drones and existing equipment to capture real-time data, completely digitizing workflows that have historically been manual and error-prone. This means facilities operate smarter, safer, and more efficiently, ultimately redefining "on-time, in full" delivery.
- If you're looking for an opportunity to contribute to truly transformative technology and make a significant impact in a vital industry, Gather AI is the place for you. We're leading the charge in the rapidly evolving robotics industry, and we invite you to join us in reshaping the global supply chain, one intelligent warehouse at a time.
- About the Team
- At Gather AI, we're not just creating software; we're pioneering a new era of warehouse intelligence.
- Are you ready to build the future of the supply chain?
- We've developed a groundbreaking, vision-powered platform that uses autonomous drones and existing equipment to capture real-time data, completely digitizing workflows that have historically been manual and error-prone.
- This means facilities operate smarter, safer, and more efficiently, ultimately redefining "on-time, in full" delivery.
- If you're looking for an opportunity to contribute to truly transformative technology and make a significant impact in a vital industry, Gather AI is the place for you.
- We're leading the charge in the rapidly evolving robotics industry, and we invite you to join us in reshaping the global supply chain, one intelligent warehouse at a time.
- This 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.
- As a Principal-level IC, you'll have real input into technical direction - not just executing on decisions, but helping make them.
This listing is sourced directly from Gather AI's careers page and normalized into a canonical job model.