Research Scientist - World-Action Foundation Model, Robotics

Applied Intuition•Sunnyvale, CA

5d•Hybrid

About The Position

Applied Intuition is seeking multiple passionate Research Scientists to join their Research Group. The group's mission is to develop cutting-edge technology for next-generation physical AI, focusing on autonomous driving and robotic generalist applications. Researchers will be supported by industry-leading tools and infrastructure, with access to extensive data and the ability to deploy their developed methods into various autonomous and robotic systems. The role involves contributing to research publications, collaborating with engineering teams for algorithm deployment, and working within a fast-paced, customer-focused culture. The company is open to all years of experience, including those with potential Tech Lead and Manager capacity.

Requirements

Strong research record in the fields of 3D vision, reconstruction and generation for robotics and autonomous systems, with publications in top-tier conferences or journals in the fields of computer vision, machine learning, and robotics.
MSc or PhD in machine learning and computer vision with autonomy and robotics applications or closely-related fields.
Passion for next-generation, scalable autonomy and robotics for real-world systems.
Strong research skills and the ability to work both independently and collaboratively on projects.
Technical experience in: Python, Pytorch, computer vision, robotics systems, and distributed machine learning model training.

Nice To Haves

Hands-on experience in at least one of the following fields: 3D foundation model and pretraining
Multi-modal foundation model
Feed-forward Gaussian splatting and reconstruction
World foundation model and generation
3D/multi-view end-to-end models for autonomous driving or robotics
Human data processing and incorporation

Responsibilities

Conduct research on pretraining world-action foundation model with various world modalities including vision and physics associated with ego actions, serving the purpose for both robot action and simulation world generation.
Diving into relevant topics such as vision-physics modality association, feed-forward Gaussian splatting, world foundation model, human data incorporation, language modality, and spatial reasoning, deformable object modeling and simulation.
Work closely with other Research Scientists and interns on research publications for submission to top-tier conferences.
Collaborate with Research Engineers and engineering teams to test and deploy algorithms to our autonomy and simulation products.