Research Scientist Computational Imaging Graduate

About the Role

The PICO Lab Technology Platform Electrical Engineering team designs silicon and electrical architecture for AR/VR platforms, optimizing system power, latency, and performance. They develop customized silicon for imaging, display, and connectivity through hardware and software co-optimization. A wearable device has a tight power and thermal envelope, and imaging, display, and connectivity all must perform within it, exceeding the capabilities of off-the-shelf solutions. Achieving the right silicon is crucial for sharp visuals, low latency, and extended battery life for a full session. This role involves architecting custom chips and hardware/software co-optimized systems to enable next-generation AR/VR.

Pico's imaging systems & human engineering team seeks a passionate and versatile imaging expert to develop next-generation imaging algorithms for a superior visual experience across Pico products, from camera to display. The ideal candidate specializes in imaging algorithm development with a deep understanding of camera and display optical and digital imaging chains. This role will be key in delivering camera capture and rendering to display experiences with optimal image quality and efficiency. Additionally, this role will contribute to defining and executing the technological and productization roadmap for imaging, shaping the future of imaging technologies and their applications in VR/MR/AR products.

As a graduate, you will have opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Successful candidates must be able to commit to an onboarding date by the end of the year. Please state your availability and graduation date clearly in your resume.

The ideal candidate has a solid foundation in multimodal AI, computer vision, computational imaging, generative AI, or computer graphics, coupled with strong curiosity and the ability to quickly explore emerging technical areas. They should be able to identify promising research, define clear technical goals and validation methods, and rapidly translate innovative ideas into working prototypes through hands-on experimentation.

In this role, you will explore multimodal foundation models, VLM/LLM post-training, reinforcement learning, context-aware modeling, generative AI, and computer graphics to develop intelligent imaging and vision algorithms. You will investigate how to incorporate contextual information into multimodal models, leverage generative models and simulation to create realistic synthetic data, and apply these technologies to real-world computer vision and computational imaging challenges. You will also work with Pico's AR/XR hardware platforms to validate algorithms and leverage AI-assisted and agentic engineering workflows to accelerate development and iteration.

Key Responsibilities

• Research and develop advanced multimodal AI, computer vision, and computational imaging algorithms.
• Explore multimodal model post-training and reinforcement learning to improve visual reasoning, decision-making, and agentic task execution.
• Develop context-aware and controllable multimodal models that integrate user intent, contextual information, and multimodal signals into model reasoning and generation.
• Investigate generative models, computer graphics, and world simulation to create realistic, controllable synthetic environments for training and evaluating vision algorithms.
• Bridge foundation models and generative AI with traditional computer vision to solve practical imaging and perception challenges.
• Rapidly prototype and validate new approaches through experimentation, automated evaluation, and real-world hardware testing.

Qualifications

Minimum Qualification(s)

• Individuals who are completing or have recently completed a PhD degree in Computer Science, Electrical or Computer Engineering, Imaging Science, Optical Engineering, Color Science, or a related field.
• Strong background in at least one of the following: multimodal learning, computer vision, computational imaging, generative modeling, or computer graphics.
• Hands-on experience developing and training deep learning models using PyTorch or similar frameworks.
• Strong programming skills in Python and familiarity with C/C++.
• Ability to independently explore research directions, design experiments, and build working prototypes.

Preferred Qualification(s)

• Experience with multimodal foundation model post-training, including reinforcement learning, reward modeling, visual reasoning, or agentic tool-use training.
• Experience designing context-conditioned or personalized multimodal models, including mechanisms for integrating contextual information into model representations, reasoning, or generation.
• Experience with multimodal agents, tool-use, planning, and execution for complex visual tasks.
• Experience in generative modeling, controllable image/video generation, computer graphics, neural rendering, or simulation-based synthetic data generation.
• Experience applying foundation models, generative AI, or synthetic data to real-world CV or computational imaging applications.
• Familiarity with camera systems, computational photography, imaging pipelines, or real-world visual system evaluation.
• Publications at CVPR, ICCV, ECCV, NeurIPS, ICLR, SIGGRAPH, or SIGGRAPH Asia are a plus.