Meta is 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 to advance the field of artificial intelligence by making fundamental advances in technologies to help interact with and understand our world.
Requirements
- 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
- Experience with the development of enterprise level AI, Machine Learning, and Deep Learning platform involving big data management and GPU compute
- 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 with training deep neural networks for key NLP tasks
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
Other
- Must obtain work authorization in 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
- Collaborate with researchers and cross-functional partners including communicating research plans, progress, and results
- Experience working and communicating cross functionally in a team environment
- Demonstrated software engineer experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub)
