Principal Applied Scientist - CV/ML, Amazon RoboticsJob ID: 2843016 | Amazon.com Services LLC
Do 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 architecturesProfound understanding of advanced vision models such as Vision Transformers (ViTs), MultiMAE, and their applicationsExpertise 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 optimizationStrong background in 3D vision, including multi-view geometry, SLAM and 3D reconstructionKey job responsibilitiesSet the technical direction for the group, bridging classical computer vision techniques with cutting-edge deep learning approachesDrive research and development of advanced perception systems, incorporating the latest advancements in self-supervised and multi-modal learningCollaborate with top-notch scientists and engineers to deliver the world's most scalable and robust robotic systemsLead the integration of vision-language models and foundation models into perception pipelinesDevelop novel approaches for few-shot learning and domain adaptation in robotic perceptionAdvance the state-of-the-art in areas such as 3D scene understanding, object pose estimation, and activity recognitionDrive 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 fieldThe 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.
BASIC QUALIFICATIONS10+ years of scientist or machine learning engineer management experiencePhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative fieldExperience building state of the art machine learning models or developing algorithmsPREFERRED QUALIFICATIONSExperience building complex software systems, especially involving deep learning, machine learning and computer vision, that have been successfully delivered to customersAmazon 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.
Posted: November 21, 2024 (Updated 1 day ago)
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