Research Scientist Intern, Language and Multimodal Research (PhD) at Meta

Seattle, Washington, United States -

Full Time

Start Date

Immediate

Expiry Date

26 Apr, 26

Salary

12134.0

Posted On

26 Jan, 26

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Generative Modeling, Deep Learning, Computer Vision, Natural Language Processing, Machine Learning, Reinforcement Learning, Python, C++, Java, Data Analysis, AI Techniques, Research, Collaboration, Algorithm Development, Statistical Analysis, Optimization

Industry

Software Development

Description

Meta was built to help people connect and share, and over the last decade our tools have played a critical part in changing how people around the world communicate with one another. With over a billion people using the service and more than fifty offices around the globe, a career at Meta offers countless ways to make an impact in a fast growing organization. Meta is seeking Research Interns to join our Meta Superintelligence Lab in the post-training modeling team across language, and multimodal. 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 generative modeling, deep learning, computer vision, natural language processing, machine learning, and reinforcement learning. Our interns have an opportunity to make core algorithmic advances and apply their ideas at an unprecedented scale. Our internships are twelve (12) to sixteen (16), or twenty-four (24) weeks long and we have various start dates throughout the year. Responsibilities Develop novel state-of-the-art generative AI 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 and training generative models of data (images, video, 3D, text, audio, and other modalities). Collaborate with researchers and cross-functional partners including communicating research plans, progress, and results. Disseminate research results. When applicable, contribute to research that can be applied to Meta product development. Minimum Qualifications Currently has or is in the process of obtaining a Ph.D. degree in Computer Science, Artificial Intelligence, Generative AI, or relevant technical field Experience with Python, C++, C, Java or other related languages Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment Experience building systems based on machine learning and/or deep learning methods Preferred Qualifications Intent to return to the 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, ACL, EMNLP, CVPR, ICCV, ECCV, or similar Experience working and communicating cross functionally in a team environment Experience in advancing AI techniques, 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 analyzing 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 $7,650/month to $12,134/month + benefits

Responsibilities

Develop novel generative AI algorithms and improve the efficiency and scalability of deployed algorithms. Collaborate with researchers and disseminate research results to advance the field of artificial intelligence.