Research Engineer - Machine Learning for Behavioral AI

About the position

Meta's Reality Labs Research (RL-R) is seeking an AI ML engineer to join the ACE team, which focuses on solving complex challenges in behavioral inference from sparse information. The team leverages multimodal, egocentric data and cutting-edge machine learning to create robust models that enhance the capabilities of Wearable AI. The role involves developing state-of-the-art AI algorithms to infer human behavior patterns, particularly those related to attention, cognition, or emotion. This includes analyzing longitudinal gaze behaviors, gestures, and vocal cues. The engineer will also create end-to-end validation platforms for wearable AI using generative AI and language models, while collaborating with system engineers to optimize these models for efficiency and latency in constrained computing environments. The position promises a dynamic work environment where learning and exploration of new technologies are encouraged, contributing to the development of innovative prototypes and technologies that could redefine human interaction with their surroundings.

Responsibilities

• Develop novel AI algorithms to infer human behavior patterns.
• Create end-to-end wearable AI experiential validation platforms.
• Optimize AI models for efficiency and latency in constrained compute platforms.
• Collaborate with Research Scientists and Engineers across RL-R.
• Engage in continuous learning and exploration of new technologies.

Requirements

• Bachelor's degree in Computer Science, Computer Engineering, or a relevant technical field, or equivalent practical experience.
• 5+ years of experience with a Bachelor's degree or 2+ years with a PhD in a relevant field.
• Experience with Python.
• Familiarity with a common machine learning framework, preferably PyTorch.
• Experience with ML computer vision.
• Proven experience in developing, maintaining, and improving complex ML systems.
• Experience with multimodal sensing platforms and signal processing.
• Knowledge of Multimodal Deep Learning approaches and research.
• Experience with Large Language Models.
• Proficiency in C++.
• Experience with non-Machine Learning computer vision, especially OpenCV.
• Familiarity with 3D engines such as Unreal or Unity.
• Experience working in Augmented Reality or Virtual Reality environments.
• Experience developing software in a research environment.