Research Scientist Intern, Multimedia Vertical Efficiency
Vor 4 Tagen
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.
Our internships are twelve (12) to twenty-four (24) weeks long and we have various start dates throughout the year.
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.
- 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.
- Perform research that enables learning the semantics of data (images, video, text, audio, and other modalities).
- Currently has or is in the process of obtaining a Ph.D. 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
- 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
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