Principal Applied Scientist - CV/ML, Amazon Robotics

DescriptionDo you want to create worldwide impact in robotics while solving challenges at the edge of robotics research? Our team in Amazon Robotics builds high-performance, real-time robotic systems that can perceive, learn, and act intelligently alongside humans—at Amazon scale. Our mission is to enable robots to interact safely, efficiently, and fluently with the clutter and uncertainty of real-world fulfillment centers. Our AI solutions enable robots to learn from their own experiences, from each other, and from humans to build intelligence that feeds itself.We hire and develop subject matter experts in AI with a focus on computer vision, deep learning, intelligent control, semi-supervised and unsupervised learning. We target high-impact algorithmic unlocks in areas such as scene and activity understanding, simultaneous localization and mapping, closed-loop control, robotic grasping and manipulation—all of which have high-value impact for our current and future fulfillment networks.We are seeking an exceptional Principal Applied Scientist to join our organization, who possesses a deep understanding of both classical computer vision techniques and state-of-the-art machine learning approaches. The ideal candidate will be hands-on, coding-proficient, and a thought leader capable of influencing the direction of ML applied to Perception and Robotics.Key qualifications:

Extensive experience in computer vision, from traditional methods (e.g., SIFT, SURF, optical flow) to modern deep learning architectures

Profound understanding of advanced vision models such as Vision Transformers (ViTs), MultiMAE, and their applications

Expertise in generative models, particularly diffusion models and their applications in robotics (e.g., diffusion policy)

Proven track record in developing scalable ML frameworks for online/offline learning, large language models, prediction systems, and continuous model optimization

Strong background in 3D vision, including multi-view geometry, SLAM and 3D reconstruction

Key job responsibilities

Set the technical direction for the group, bridging classical computer vision techniques with cutting-edge deep learning approaches

Drive research and development of advanced perception systems, incorporating the latest advancements in self-supervised and multi-modal learning

Collaborate with top-notch scientists and engineers to deliver the world's most scalable and robust robotic systems

Lead the integration of vision-language models and foundation models into perception pipelines

Develop novel approaches for few-shot learning and domain adaptation in robotic perception

Advance the state-of-the-art in areas such as 3D scene understanding, object pose estimation, and activity recognition

Drive ideas to products using a comprehensive toolset including deep learning, active learning, and computer vision (camera selection, camera calibration, instance and semantic segmentation, pose estimation, activity understanding)

Mentor and guide team members in adopting best practices and staying current with rapid advancements in the field

The ideal candidate will have a Ph.D. in Computer Science, Electrical Engineering, or a related field, with a strong publication record in top-tier conferences (CVPR, ICCV, NeurIPS, ICML, etc.) and practical experience applying advanced ML techniques to real-world robotics problems.A day in the lifeAmazon offers a full range of benefits for you and eligible family members, including domestic partners and their children. 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

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

10+ years of scientist or machine learning engineer management experience

PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field

Experience building state of the art machine learning models or developing algorithms

Preferred Qualifications

Experience building complex software systems, especially involving deep learning, machine learning and computer vision, that have been successfully delivered to customers

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, 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.Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $179,000/year in our lowest geographic market up to $309,400/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.