ByteDance
ByteDance

Camera System Architect - PICO Lab VST - San Jose

RoleSystems
LevelMid Level
LocationSan Jose, Canada, United States
WorkOn-site
TypeRegular
PostedToday
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About the role

About team:
The VST/camera team focuses on finding low power, high image quality solutions for AR/VR camera systems, including developing CMOS sensors, novel optical/imaging sensors, ultra-compact camera module technologies, camera lens design, and algorithms. The team is vertically integrating HW/SW for system optimization, shaping the AI experience for the future.

Responsibilities:

  • Define and own the system architecture of end-to-end camera solutions, spanning optics, image sensors, compute platforms, mechanics, algorithms, and software.
  • Drive hardware–software co-design to optimize system-level performance, power, cost, and scalability.
  • Lead system-level imaging and perception performance definition, evaluation, and optimization across hardware and AI-based processing.
  • Design and integrate computer vision and AI algorithms into production camera systems.
  • Evaluate and integrate emerging imaging and AI technologies to maintain product competitiveness.

Requirements:

  • Minimum Qualifications

  • Master’s or PhD in Optical Engineering, Electrical Engineering, Computer Science, Computational Imaging, or related fields.

  • 3+ years of experience in camera or imaging system development, with scope spanning both hardware and software.

  • Proven full-cycle product development experience, including prototype builds, EVT, DVT, and mass production, in a hardware product environment.

  • Leverage AI-assisted engineering tools (LLMs, VLMs) to accelerate design iteration, analysis, debugging, and technical decision-making.

  • Strong system-level thinking, first-principles reasoning, and ability to make and defend complex technical trade-offs.

  • Demonstrated ability to work effectively across cross-functional engineering teams.

  • Preferred Qualifications

  • Familiarity with SoC / ISP / NPU architectures and model-to-hardware adaptation or optimization.

  • Hands-on experience with computer vision and machine learning, particularly in real-time or resource-constrained systems.

  • Prior ownership of camera system architecture or subsystem technical leadership.

About ByteDance

San Jose

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