Research Scientist Graduate (Computational Imaging-PICO) - 2027 Start (PhD)

The PICO Lab Technology Platform Electrical Engineering team designs the silicon and electrical architecture behind AR/VR platforms, optimizing system power, latency, and performance. We 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 have to perform inside it, which is more than off-the-shelf solutions can manage. Getting the silicon right is what delivers sharp visuals, low latency, and a battery that lasts through a full session.

You will architect the custom chips and hardware and software co-optimized systems that make next-generation AR/VR physically possible.

About Team: Pico's imaging systems & human engineering team is looking for a passionate and versatile imaging expert to work on next generation imaging algorithms that will deliver the top 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, and will play a key role in delivering camera capture and rendering to display experience with the best image quality and efficiency. This role will also contribute to the definition and execution of technological and productization roadmap in imaging to shape the future of imaging technologies and their applications in VR/MR/AR products.

We are looking for talented individuals to join our team. As a graduate, you will get 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, together 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.

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.Minimum Qualification(s)
• Individuals who are completing or have recently completed 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.