Meta is seeking Research Interns to join Monetization Ranking & AI Foundations to serve the best personalized ads to people, maximizing their personal utility and advertiser value
Requirements
Experience with deep learning frameworks such as Pytorch or Tensorflow
Experience with Python, C++, C, Java, or other related languages
Experience with research and building systems based on machine learning and/or deep learning methods
Currently has or is in the process of obtaining a Ph.D. degree in Machine Learning, Artificial Intelligence, Computer Science, Information or Multimedia Retrieval, Computer Vision, Natural Language Processing, Reinforcement Learning, Optimization, Computational Statistics, Applied Mathematics, or related technical fields
Demonstrated software engineer experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub)
Experience manipulating and analyzing complex, high-volume, high-dimensionality data from varying sources for large-scale training
Responsibilities
Conduct state-of-the-art research to advance the science and technology of Machine Learning and Artificial Intelligence
Develop novel algorithms and corresponding systems, leveraging various AI and ML techniques
Analyze and improve efficiency, scalability, and stability of corresponding deployed algorithms
Collaborate with researchers and engineers across varied disciplines, including communicating research plans, progress, and results
Publish research results and contribute to research that can be applied to Meta product development
Other
Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment
Intent to return to degree program after the completion of the internship/co-op
Currently has or is in the process of obtaining a Ph.D. degree
Demonstrated experience and self-driven motivation in solving analytical problems using quantitative approaches
Experience working and communicating cross functionally in a team environment
