Camera System Architect - Pico Lab Vst - San Jose

ByteDance · Big Tech · San Jose, CA · R&D

This role is for a Camera System Architect at ByteDance's PICO Lab, focusing on AR/VR camera systems. The architect will define and own end-to-end camera solutions, driving hardware-software co-design and integrating computer vision and AI algorithms into production systems. The role requires experience in camera/imaging system development, full-cycle product development, and leveraging AI-assisted engineering tools.

What you'd actually do

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.

Skills

Required

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.

Nice to have

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.

What the JD emphasized

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

Read full job description

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.

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.