Sr. Applied Scientist - Computer Vision, Amazon Robotics

Amazon; San Francisco (CA); On-site; USD 167,100 - 226,100; Full time

Job summary

Amazon Robotics is seeking a Senior Applied Scientist to advance 3D perception systems for real-time robotic platforms. You will develop scalable pipelines, optimize inference on ARM-based edge hardware, and deploy models that operate under strict latency constraints, contributing to perception, planning, and control in fulfillment centers.

The role emphasizes deep learning, transformer-based architectures, and large-scale data generation, with mentorship and collaboration across science,

Qualifications

• PhD or Master’s with 6+ years of applied research experience.
• 4+ years building machine learning models for business applications.
• Experience with 3D computer vision and robotics for real-time deployment.
• Proficiency in Java, C++, Python or related languages.

Responsibilities

• Architect, design, and implement 3D perception models for semantic occupancy prediction and scene completion on robotic platforms.
• Own end-to-end model lifecycle: scalable training, optimized inference latency on edge processors, production deployment.
• Design and scale pseudo-ground-truth data generation pipelines to produce training samples using SageMaker infrastructure.
• Drive multi-view perception integration by fusing multiple view camera inputs for robust 3D reconstruction.
• Mentor applied scientists and engineers, raise the technical bar, foster scientific rigor.

Skills

3D CV

Deep learning

Edge deployment

Python

C++

Education

PhD or MSc

Tools

ONNX

TensorRT

Job description

Sr. Applied Scientist - Computer Vision, Amazon Robotics

Job ID: 10467967 | Amazon.com Services LLC

Overview

Join Amazon Robotics to build high-performance, real-time robotic systems that perceive, learn, and act intelligently at scale. Our mission is to enable robots to interact safely, efficiently, and fluently in high-density fulfillment centers. We focus on 3D perception, computer vision, deep learning, and generative modeling to unlock high-impact algorithmic advancements in areas such as 3D scene understanding, semantic occupancy prediction, multi-view 3D reconstruction, depth estimation, and real-time inference.

We are seeking a passionate, hands-on Senior Applied Scientist who will work deeply with code and algorithms, building scalable 3D perception systems across semantic scene completion, encoder-decoder and transformer architectures (e.g., VoxFormer, MonoScene), voxelized occupancy prediction, panoptic and instance segmentation, depth estimation, point cloud processing, and multi-view fusion. You will contribute to R&D of advanced 3D perception pipelines enabling robots to reason about occluded and partially observed environments and help translate ideas into products using 3D generative models, query-based transformers, and scalable pseudo-ground-truth data generation.

Key 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—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 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. Benefits can vary by location and employment status. 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.

If you are not sure that every qualification on the list above describes you exactly, we still want to hear from you. At Amazon, we value people with unique backgrounds and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply.

Basic Qualifications

• 4+ years of building machine learning models for business applications
• 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

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, WA, Seattle - 167,100.00 - 226,100.00 USD annually

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.