Research Scientist Intern PhD, Applied Research Responsibilities
Develop novel state-of-the-art generative AI algorithms and corresponding systems, leveraging various deep learning techniques
Help analyze and improve safety and robustness of corresponding deployed algorithms based on the project
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
Disseminate research 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 Ph.D. degree in Computer Science, Computer Vision, Audio Processing, Artificial Intelligence, Generative AI, 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
Research experience in machine learning, deep learning, computer vision and/or natural language processing
Experience with Python, C++, C, Java or other related languages
Experience with deep learning frameworks such as Pytorch or Tensorflow
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, ICLR, AAAI, RecSys, KDD, IJCAI, CVPR, ECCV, ACL, NAACL, EACL, ICASSP, or similar
Experience working and communicating cross functionally in a team environment
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 explainable AI methods and topics around LLM safety alignment
Demonstrated software engineer experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub)
