Applied Scientist, FAR (Frontier AI & Robotics)

Amazon•San Francisco, CA

About The Position

Join the next revolution in robotics at Amazon's Frontier AI & Robotics team, where you'll work alongside world-renowned AI pioneers to push the boundaries of what's possible in robotic intelligence. As an Applied Scientist, you'll be at the forefront of developing breakthrough foundation models that enable robots to perceive, understand, and interact with the world in unprecedented ways. You'll drive independent research initiatives in areas such as perception, manipulation, scene understanding, sim2real transfer, multi-modal foundation models, and multi-task learning, designing novel algorithms that bridge the gap between state-of-the-art research and real-world deployment at Amazon scale. In this role, you'll balance innovative technical exploration with practical implementation, collaborating with platform teams to ensure your models and algorithms perform robustly in dynamic real-world environments. You'll have access to Amazon's vast computational resources, enabling you to tackle ambitious problems in areas like very large multi-modal robotic foundation models and efficient, promptable model architectures that can scale across diverse robotic applications. At Frontier AI & Robotics, we're not just advancing robotics – we're reimagining it from the ground up. Our team is building the future of intelligent robotics through ground breaking foundation models and end-to-end learned systems. We tackle some of the most challenging problems in AI and robotics, from developing sophisticated perception systems to creating adaptive manipulation strategies that work in complex, real-world scenarios. What sets us apart is our unique combination of ambitious research vision and practical impact. We leverage Amazon's massive computational infrastructure and rich real-world datasets to train and deploy state-of-the-art foundation models. Our work spans the full spectrum of robotics intelligence – from multimodal perception using images, videos, and sensor data, to sophisticated manipulation strategies that can handle diverse real-world scenarios. We're building systems that don't just work in the lab, but scale to meet the demands of Amazon's global operations. Join us if you're excited about pushing the boundaries of what's possible in robotics, working with world-class researchers, and seeing your innovations deployed at unprecedented scale.

Requirements

PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
Experience programming in Java, C++, Python or related language
Experience building machine learning models or developing algorithms for business application
Experience in patents or publications at top-tier peer-reviewed conferences or journals
Experience applying theoretical models in an applied environment
Experience developing and implementing deep learning models
Track record of solving complex technical problems
Experience using Unix/Linux

Nice To Haves

First-author publications at major or top-tier ML / robotics conferences (NeurIPS, ICML, ICLR, CVPR, ICCV, RSS, CoRL)
Experience with foundation models or large language models
Background in computer vision, robotics, or related fields
Experience with sim2real transfer or multi-task learning
Familiarity with distributed training systems
Track record of deploying ML models in production environments
Experience with large-scale machine learning systems
Extensive programming skills in Python and PyTorch/JAX

Responsibilities

Design and implement novel deep learning architectures that push the boundaries of what robots can understand and accomplish
Drive independent research initiatives in robotics foundation models, focusing on breakthrough approaches in perception, and manipulation, for example open-vocabulary panoptic scene understanding, scaling up multi-modal LLMs, sim2real/real2sim techniques, end-to-end vision-language-action models, efficient model inference, video tokenization
Lead technical projects from conceptualization through deployment, ensuring robust performance in production environments
Collaborate with platform teams to optimize and scale models for real-world applications
Contribute to the team's technical strategy and help shape our approach to next-generation robotics challenges