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Applied Vision Scientist, XR Perception - PICO Lab (San Jose)

ByteDance
  • 🇺🇸 United States
  • On-site
  • 1 month ago
  • AI
  • Python
  • MATLAB
  • C++
  • AI/ML
  • Temporal
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About Team

PICO's Imaging Systems & Human Engineering team is seeking a passionate and versatile Vision Scientist to help shape the next generation of perception-driven computational camera and display systems for PICO XR products. The ideal candidate has a deep understanding of vision science, strong command of psychophysics methods and statistical theory, and solid computational modeling skills. Experience with eye tracking, EEG/EOG, and other biosensing modalities, as well as hands-on experience with XR products and AI agents, is highly valued. The ideal candidate is also able to thrive in a dynamic, fast-paced environment. In this role, you will play a key part in defining perceptual specifications, running rigorous user studies, and building the models, prototypes, and features that optimize user experience across PICO's imaging products.

Responsibilities

  • Define novel, product-critical perceptual specifications and metrics that quantify user experience in visual quality, visual comfort, and human performance for AR/VR products, and drive their adoption in system architecture and product requirements.
  • Design, conduct, and analyze psychophysics experiments and user studies to characterize human visual perception, validate novel features, and inform product decisions with statistically rigorous evidence.
  • Implement and develop XR-related features, leveraging multimodal sensor data and biometric signals (e.g., eye tracking, EEG/EOG, and other biosensing data), from algorithm prototyping through integration and validation.
  • Develop and maintain simulation platforms, computational models, and prototypes to accelerate hardware design iterations and software optimizations.
  • Apply perception science and early vision modeling to identify system limitations of next-generation display and imaging systems, and translate findings into actionable architecture specifications.

Minimum Qualification(s)

  • Advanced degree in Vision Science, Perceptual Psychology, Computational Neuroscience, Optometry, Human Factors, Imaging Science, Color Science, Optics, Computer Science, or a related field.
  • 5+ years of experience (inclusive of graduate school research experience) in related fields.
  • Deep understanding of the human visual system, visual perception, and image quality concepts.
  • Strong familiarity with psychophysics methods and experiment design, including stimulus design, adaptive procedures, and validation through user studies.
  • Strong background in data analysis and statistical theory, with experience applying rigorous statistical methods to behavioral and perceptual data.
  • Solid knowledge of computational modeling, including building and validating models of visual perception or human performance.
  • Experience working with large-scale, complex datasets and data analysis pipelines, plus proficiency in one or more scripting, modeling, data analysis, or prototyping languages such as Python, MATLAB, or C++.

Preferred Qualification(s)

  • Experience with eye tracking (ET), EEG, EOG, or other biosensing technologies, including signal acquisition, processing, and analysis, and their applications in perception research or product features.
  • Experience working with XR products (AR/VR/MR), including understanding of hardware–software imaging and display system architecture.
  • Experience working with AI agents and platforms or integrating AI/ML tools into research and development workflows.
  • Experience in engineering productization and delivery, including translating research prototypes into production-ready solutions.
  • Expertise in one or more areas of visual comfort, spatio-temporal vision, visual optics, binocular vision, or visual neuroscience.
  • Experience in the related consumer electronics industry and understanding of hardware-software imaging system architecture.

Applied Vision Scientist, XR Perception - PICO Lab (San Jose) · ByteDance

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