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Meta Reality Labs is looking for PhD-level interns to join our world-class team advancing imaging and computer vision technology for the next generation of AR/VR systems. In this role, you will work on cutting-edge research and development of novel algorithms, architectures, and tools to solve real-world problems in imaging and computer vision that integrate with specialized hardware.As a Research Scientist Intern, you will collaborate with cross-functional teams of researchers, engineers, and hardware specialists to design, prototype, and optimize innovative computer vision models and algorithms. You will play a key role in evaluating image and video quality, pushing the boundaries of machine learning models, and developing techniques that interact seamlessly with custom hardware to drive state-of-the-art performance.Our internships are twelve (12) to twenty-four (24) weeks long, and we have various start dates throughout the year.

Research Scientist Intern, Imaging and Computer Vision (PhD) Responsibilities:

• Develop novel algorithms for image processing, computer vision, and multimodal data fusion.
• Design and prototype new architectures for real-time image and video processing in AR/VR systems.
• Develop machine learning models that interact efficiently with specialized imaging hardware, optimizing for performance, energy efficiency, and scalability.
• Perform image and video quality evaluations using both objective and subjective methods.
• Build new tools and workflows for evaluating and improving visual quality and computational efficiency of vision systems.
• Collaborate with hardware teams to co-design algorithms that leverage specialized accelerators or custom silicon for optimized performance.
• Conduct cutting-edge research to publish at top-tier conferences and workshops in imaging, computer vision, and machine learning.
• Communicate results and progress to both technical and non-technical stakeholders

Minimum Qualifications:

• Currently has, or is in the process of obtaining, a PhD degree in Computer Science, Electrical Engineering, machine learning, computer vision or related field.
• Experience in developing and implementing advanced algorithms for imaging, computer vision, or machine learning applications.
• Experience in Python and/or MATLAB, and C++.
• Familiarity with machine learning frameworks such as PyTorch, TensorFlow, or other related tools.
• Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment.

Preferred Qualifications:

• Intent to return to degree-program after the completion of the internship/co-op.
• Proven track record of achieving significant results, as demonstrated by first-authored publications at leading workshops or conferences in imaging, computer vision, or machine learning (e.g., CVPR, ICCV, ECCV, NeurIPS, ICML).
• Experience with designing computer vision algorithms optimized for specialized hardware such as GPUs, DSPs, or custom ASICs.
• Strong understanding of image and video quality metrics and evaluation methodologies.
• Experience with software-hardware co-design and developing models that interact with low-level system components
• Ability to design new tools for data processing, visualization, and performance evaluation.
• Familiarity with state-of-the-art techniques in computational imaging, video compression, 3D reconstruction, or AR/VR applications.
• Experience working and communicating cross functionally in a team environment

About Meta:
Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.