Research Scientist Intern

About the Role

This is a research internship focused on low-power real-time reconstruction of scene geometry for AR/VR. The role addresses open questions regarding depth estimation and processing strategies for a glasses power budget and the potential for a single lightweight scene representation to serve multiple downstream applications.

Key Responsibilities

• Plan and execute research to advance the state of the art in low-power, real-time scene reconstruction for AR/VR, including depth estimation, occlusion, and geometric scene understanding.
• Explore the extent to which a shared, learned scene representation can serve multiple downstream consumers at different latency and accuracy points.
• Define evaluation methodology and run experiments measuring geometric accuracy, temporal stability, rendering distortion, latency, and compute and power cost on real multi-sensor device captures.
• Collaborate with researchers and engineers to assess feasibility within headset and glasses power envelopes.
• Document and present findings, and contribute to publications and patents where the results warrant it.

Requirements & Tech Stack

• Knowledge and hands-on experience in at least one of:
• depth or stereo estimation
• 3D reconstruction (TSDF, implicit or neural fields, Gaussian splatting)
• video or instance segmentation
• neural scene representations
• Experience designing and running quantitative experiments.
• Experience communicating technical results.
• Experience with C++.
• Experience with profiling or optimizing real-time computer vision or graphics pipelines.
• Experience working in a Unix environment.
• Experience reasoning about compute and power budgets as a first-class design constraint.

Preferred Qualifications

• Intent to return to a degree-program after the completion of the internship.
• Proven track record of achieving significant results (grants, fellowships, patents, first-authored publications at leading conferences like CVPR/ECCV/ICCV, SIGGRAPH/SIGGRAPH Asia, 3DV, ICLR, NeurIPS, etc.).
• Experience with efficient or on-device inference: quantization, distillation, pruning, or deployment to mobile NPU, DSP or GPU targets.
• Experience with multi-sensor fusion across heterogeneous sensors (RGB, IR/CV cameras, time-of-flight), including camera calibration and cross-sensor registration.
• Experience with temporal filtering and state estimation over scene state.
• Familiarity with AR/VR passthrough, reprojection, occlusion rendering, or SLAM and scene reconstruction.

General Qualifications

• Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment.