Research Scientist Intern, Representation Learning (PhD)

We are committed to advancing the field of artificial intelligence by making fundamental advances in technologies to help interact with and understand our world. We are seeking individuals passionate in areas such as deep learning, computer vision, audio and speech processing, natural language processing, machine learning, reinforcement learning, computational statistics, and applied mathematics. Our interns have an opportunity to make core algorithmic advances and apply their ideas at an unprecedented scale. The DINO team designs algorithms for learning state-of-the-art visual representations. The DINO series of models is widely used as a foundation model across various vision applications and domains. As part of the team, interns have the opportunity to make an impact on the next generation of DINO models. We offer twelve (12) to twenty-four (24) weeks long internships and we have various start dates throughout the year.

Responsibilities

Develop novel state-of-the-art representation learning algorithms and corresponding systems, leveraging various deep learning techniques.

• Based on the project, help analyze and improve efficiency, scalability, and stability of corresponding deployed algorithms.

• Perform research to advance the science and technology of intelligent machines.

• Perform research that enables learning the semantics of data.

• Collaborate with researchers and cross-functional partners including communicating research plans, progress, and results.

• Contribute to research that can be applied to Meta product development.

Minimum Qualifications

• Currently has or is in the process of obtaining a PhD degree in Computer Science, Computer Vision, Artificial Intelligence, or relevant technical field

• Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment

• Experience with Python-based development and PyTorch

• Experience building systems based on machine learning and/or deep learning methods

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 (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, ACL, or similar), and grants, fellowships, or patents

• Experience working and communicating cross functionally in a team environment

• Experience in advancing AI techniques in machine learning, including core contributions to open source libraries and frameworks in machine learning

• Publications or experience in machine learning, AI, computer vision, optimization, computer science, statistics, applied mathematics, or data science

• Experience solving analytical problems using quantitative approaches

• Experience setting up ML experiments and analyze their results

• Experience manipulating and analyzing complex, large scale, high-dimensionality data from varying sources

• Experience in utilizing theoretical and empirical research to solve problems

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.

Equal Employment Opportunity

Meta is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. You may view our Equal Employment Opportunity notice here.