Research Scientist Intern, Computer Vision
Il y a 7 mois
**Research Scientist Intern, Computer Vision (PhD) Responsibilities**:
- Develop novel state-of-the-art computer vision 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 (images, video, text, audio, and other modalities).
- Collaborate with researchers and cross-functional partners including communicating research plans, progress, and results.
- Publish research results and 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 country of employment at the time of hire and maintain ongoing work authorization during employment.
- Experience with Python, C++, C, Java or other related language.
- 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 grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences such as NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, ACL or similar.
- Experience working and communicating cross functionally in a team environment.
- Experience in advancing AI techniques in computer vision, including core contributions to open source libraries and frameworks in computer vision.
- 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.
- Experience with deep learning frameworks.
**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.
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