Drimva

ByteDance

Research Scientist Intern - Multimodal Sensing & On-Device Perception - Global Frontier Tech Recruitment Program - 2027 Start (PHD)

San Jose, California · Internship · Posted Oct 28, 2026

Education
Currently pursuing a PhD in Computer Science, Electrical Engineering, Optical Engineering, Applied Mathematics, Physics, or a related technical field.

About the job

Research sensor-to-model architectures that combine sensing and computation to improve energy-efficient visual perception for intelligent hardware and AI agents.

What you'll do

  • Design and prototype imaging architectures that move computation closer to sensors, such as near-sensor processing, event-driven capture, and learned pixel-level compression.
  • Build and characterize imaging pipelines from optics and sensors through ISP to perception models, identifying opportunities to reduce wasted data and add useful processing.
  • Use foundation-model needs to guide sensing design and develop or adapt vision models around hardware power, bandwidth, and latency constraints.

What they ask for

  • Currently pursuing a PhD in Computer Science, Electrical Engineering, Optical Engineering, Applied Mathematics, Physics, or a related technical field.
  • Strong research background in computer vision and machine learning, including hands-on model training.
  • Experience in at least one of sequence modeling, language modeling, efficient neural network design, or signal processing.

Nice to have

  • Research publications in CVPR, ICCV, ECCV, NeurIPS, ICLR, SIGGRAPH, or similar venues.
  • Hands-on active-sensing hardware prototyping, or familiarity with on-device/on-sensor computing, embedded ML deployment, and hardware/software co-design.

Tools

VLM, LLM, ISP, CVPR, ICCV, ECCV, NeurIPS, ICLR

AI focus

Co-design sensing hardware and machine-vision algorithms for efficient perception, informed by vision-language models, LLMs, and world models.

Model-written summary · the original posting is authoritative

First seen Oct 28, 2026 · Last verified Nov 5, 2026 (UTC)