Research Engineer, Machine Perception (Project Aria)

Meta•Redmond, WA

5d•$154,003 - $217,000

About The Position

Meta Reality Labs Research (RL Research) brings together a multidisciplinary, cross-discipline R&D team with the shared goal of developing the next generation of AR and VR technologies. The Project Aria team works on complex, open problems in machine perception — building the complete stack from sensor design through state estimation, tracking, calibration, and 3D reconstruction to novel scene representations. We are seeking a Research Engineer to develop and advance the algorithms and software systems that turn cutting-edge perception research into robust, deployable technology on future AR/VR devices.

Requirements

Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
6+ years of C++ or Python experience building and shipping software systems
Experience understanding, developing, and analyzing complex systems
Experience with statistical analysis of data and mathematical modeling
Interpersonal experience: cross-group and cross-functional collaboration
Must obtain and maintain work authorization in the country of employment during employment

Nice To Haves

Master's or PhD in Computer Science, Computer Vision, Machine Learning, or a related field
Experience taking research prototypes to deployed products on constrained/embedded hardware
Track record of results via first-authored publications at leading venues (CVPR, ICCV/ECCV, NeurIPS, ICLR, SIGGRAPH) or widely used open-source contributions
Broad understanding of the full machine-perception pipeline, from sensors to high-level algorithms
Experience with 3D computer vision, SLAM, vision-language models (VLMs), or multimodal learning

Responsibilities

Plan and execute innovative engineering development to advance the state-of-the-art in machine perception for AR/VR — including vision-language models (VLMs), multimodal and egocentric scene understanding, and foundation models
Develop and prototype tightly integrated hardware/software technologies, from research prototype to on-device deployment
Analyze and improve the efficiency, accuracy, scalability, and stability of currently deployed systems
Design, implement, and evaluate algorithms against real sensor data and experimental hardware
Build tooling and infrastructure (data pipelines, replay/evaluation systems, benchmarks) that accelerate the research team
Collaborate with researchers and engineers across disciplines throughout the project lifecycle, and clearly communicate agenda, progress, and results