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Camera System Architect- PICO Lab VST - San Jose

ByteDance

Skills

Required

  • camera or imaging system development
  • product development
  • EVT
  • DVT
  • mass production
  • LLMs
  • VLMs
  • accelerate design iteration, analysis
  • debugging
  • technical decision-making

Preferred

  • optimization
  • computer vision
  • SoC / ISP / NPU architectures
  • model-to-hardware adaptation
  • machine learning
  • real-time or resource-constrained systems
  • camera system architecture / subsystem
  • AI
  • algorithms

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

  • 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

  • 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.

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