Sr. Applied Scientist - Computer Vision, Amazon Robotics

Key job responsibilities

• Architect, design, and implement 3D perception models - including encoder-decoder networks, query-based transformers, and generative architectures- for semantic occupancy prediction and scene completion on robotic platforms.
• Own the end-to-end model lifecycle: develop scalable training pipelines, optimize inference latency for ARM-based edge processors, and deploy production models that meet real-time performance targets.
• Design and scale pseudo-ground-truth data generation pipelines - both heuristic-based and learning-based (e.g., SAM3D, shape completion) to produce curated training samples using SageMaker infrastructure.
• Drive multi-view perception integration by fusing multiple view camera inputs for robust 3D reconstruction in partially observed and occluded bin environments.
• Influence the team's technical strategy and contribute to the long-term vision and roadmap for 3D perception in fulfillment robotics.
• Partner with cross-functional stakeholders across engineering, science, and operations teams to define requirements, iterate on system design, and deliver end-to-end solutions from research prototype to production deployment.
• Maintain high standards by participating in design and code reviews, designing for fault tolerance and operational excellence, and creating mechanisms for continuous improvement.
• Prototype and validate concepts through simulation, synthetic data evaluation, and live robotic workcell testing using 3D metrics (mIoU, IoU) and affordance-based evaluation frameworks.
• Mentor applied scientists and engineers, raise the technical bar, and foster a culture of scientific rigor and rapid experimentation.

A day in the life

• Amazon offers a full range of benefits for you and eligible family members, including domestic partners.
• Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment.
• The benefits that generally apply to regular, full-time employees include: Medical, Dental, and Vision Coverage, Maternity and Parental Leave Options, Paid Time Off (PTO), 401(k) Plan.

Basic Qualifications

• 4+ years of building machine learning models for business application experience
• PhD, or Master's degree and 6+ years of applied research experience
• Experience programming in Java, C++, Python or related language
• Experience with neural deep learning methods and machine learning
• Demonstrated expertise in 3D computer vision and deep learning for robotics - spanning semantic scene completion, occupancy prediction, depth estimation, multi-view reconstruction, and real-time model deployment on edge hardware.

Preferred Qualifications

• Publications in top-tier venues (CVPR, ICCV, ECCV, NeurIPS, 3DV, CoRL) in 3D scene understanding, shape completion, or occupancy prediction.
• Deep expertise in generative 3D models, vision transformers, and semantic scene completion architectures.
• Experience building large-scale pseudo-ground-truth or synthetic data pipelines (100K+ samples).
• Proficiency in real-time model optimization (ONNX/TensorRT) and deployment on edge hardware.
• Strong foundation in 3D geometry, multi-view reconstruction, and sensor fusion.
• Track record shipping ML models into production robotic systems with hard latency constraints.
• Effective communicator across science, engineering, and operations stakeholders in fast-paced environments.