Research Engineer

Meta•Pittsburgh, PA

1d•$121,992 - $143,000

About The Position

Meta Platforms, Inc. (Meta), formerly known as Facebook, Inc., builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps and services like Messenger, Instagram, and WhatsApp further empowered billions of people around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. To apply, click “Apply to Job” online on this web page.

Requirements

Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta
Master's degree in Entertainment Technology, Computer Graphics, Computer Science, Engineering, Machine Learning or a related field
Experience in developing an end-to-end ML pipeline that includes data preprocessing, model development, deployment, and optimizations
Algorithms, data structures, or system software
Solving analytical problems using quantitative approaches
Experience devising data-driven models of human behavior
Python, PyTorch, C++

Nice To Haves

Experience with code (CPU/GPU) profiling and runtime optimizations
Experience in managing and operating computers in Linux environments
Experience working independently, handling concurrent projects where timelines may be ambiguous or changing, and prioritizing the team's roadmap and deliverables by balancing required effort with resulting impact
Publication in leading workshops or conferences such as CVPR, ECCV, ICCV, SIGGRAPH, ICCP, RSS, ICRA, etc
Experience in database and data management systems at scale

Responsibilities

Collaborate with diverse and interdisciplinary researchers, engineers, and designers to conceptualize, build, and test novel digital humans and avatars technologies
Support the realization of research outcomes into code and experiences through reusable tools, extensible plug-ins, and clear readable code
Learn constantly, dive into new areas with uncharted technologies, and navigate ambiguous problem spaces by scoping research questions, prototyping solutions, and iterating based on findings