AI Research Scientist - Machine Learning for Behavioral AI

Meta Platforms, Inc.•Redmond, WA

35d

About The Position

Meta's Reality Labs Research (RL-R) brings together a world-class team of researchers, developers, and engineers to create the future of Mixed Reality (MR), Augmented Reality (AR), and Wearable Artificial Intelligence (AI). Within RL-R, the ACE team solves complex challenges in behavioral inference from sparse information. We leverage multimodal, egocentric data and cutting edge machine learning to deliver robust, efficient models that serve everyone. Our research provides core building blocks to unlock intuitive and helpful Wearable AI, empowering everyone to harness the superpowers of this emerging technology in their daily lives. We are looking for an experience AI Research Scientist to join us in this initiative. In this role, you will work closely with Research Scientists and Engineers from across RL-R to develop novel state-of-the-art AI algorithms to infer human behavior patterns, with an emphasis on those that inform attention, cognition or emotion. Examples include longitudinal gaze behaviors, gestures, or vocal cues. You will develop end-to-end wearable AI experiential validation platforms using cutting edge generative AI and language models to validate the impact of these signals. Further, you will work with system engineers to optimize these models for efficiency and latency in constrained compute platforms. You will learn constantly, dive into new areas with unfamiliar technologies, and embrace the ambiguity of AR, VR, and AI problem solving. Together, we are going to build cutting-edge prototypes, technologies, and toolsets that can define a paradigm shift in how we interact with our surroundings. We invite you to step into the adventure of a lifetime, as we make science fiction real and change the world.

Requirements

Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
PhD degree in Computer Science, Human-Computer Interaction, or related field plus 2+ years of experience
Proven track record of solving complex challenges with multimodal ML as demonstrated through grants, fellowships, patents, or publications at conferences like CVPR, NeurIPS, CHI, or equivalent
3+ years of experience with Python
Experience with a common machine learning framework like PyTorch
Experience with ML computer vision
Experience with multimodal sensing platforms, data collection, multimodal signal processing and analysis, and converting raw sensor streams into robust models solving complex tasks

Nice To Haves

Experience with C++
Experience with biosignals, behavioral signals, or egocentric data from wearable sensors
First or lead author publications in computer vision, machine learning or computer graphics peer-reviewed conferences (e.g. CVPR, ECCV, ICCV, CHI, NeurIPS, ICLR, etc.).
Experience with Large Language Models
Experience with non-ML computer vision, especially with OpenCV
Experience with Multimodal Deep Learning approaches and research
Experience working in Augmented Reality/Virtual Reality
PhD degree in Computer Science or related field plus 3+ years experience
Experience with 3D engines such as Unreal or Unity
Experience developing software in a research environment

Responsibilities

Using data from wearable devices, employ state-of-the-art AI algorithms to infer human behavior patterns that inform attention, cognition or emotion. Examples include longitudinal gaze behaviors, gestures, or vocal cues
Develop data collection strategies, benchmarks, and metrics to validate and improve efficiency, scalability, and stability of these models
Collaborate with researchers and engineers across diverse disciplines through all stages of project development to identify gaps, build solutions, and transfer technology
Contribute to research that can eventually be applied to Meta products and services and run on billions of media items every day
Create tools, infrastructure, and documentation to accelerate research
Perform code reviews that improve software engineering quality
Learn constantly, dive into new areas with unfamiliar technologies, and embrace the ambiguity of Augmented Reality/Virtual Reality problem solving

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