Research Scientist Intern, Monetization Generative AI - LLM (PhD) Responsibilities
Perform research to advance the science and technology of intelligent machines
Develop novel and accurate NLP algorithms and systems, leveraging Deep Learning and Machine Learning on big data resources
Analyze and improve efficiency, scalability, and stability of various deployed systems
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 Ph.D. degree in Computer Science, Artificial Intelligence, Natural Language Processing, Speech Recognition, Sentiment Analysis, Computer Vision, 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 with deep learning frameworks such as Pytorch or Tensorflow
Experience building systems based on machine learning, deep learning methods, or natural language processing
Preferred Qualifications
Experience with the development of enterprise level AI, Machine Learning, and Deep Learning platform involving big data management and GPU compute
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 with Large Language Models, on top of the latest research of text only input and multimodal input to large language models
Experience with ML areas such as Natural Language Processing, Speech, Multimodal Reasoning & Retrieval, Visual Question & Answering
Experience building systems based on machine learning, reinforcement learning and/or deep learning methods
Experience working and communicating cross functionally in a team environment
Experience with training deep neural networks for key NLP tasks
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
Intent to return to degree program after the completion of the internship/co-op
