PhD AI Research Scientist Intern, Video Recommendations

Meta; Menlo Park (CA); On-site; USD 85,000 - 141,000; Full time

Job summary

Meta invites AI Research interns to join the Video Recommendations team on Facebook, focusing on end-to-end ML/NLP problems at the intersection of Product, ML, and Infra. Interns collaborate with Researchers and Software Engineers across start-to-finish challenges, framing practical questions into rigorous ML solutions.

The role spans 12 to 24 weeks with multiple start dates, offering exposure to cutting-edge research and real-world product impact on video content recommendations.

Qualifications

• Currently has or is in the process of obtaining a Ph.D. in Computer Science, AI, NLP, Speech Recognition, Sentiment Analysis, CV, or related 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.
• Familiarity with machine learning and common deep learning architectures.

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.

Skills

Python

C++

C

Java

PyTorch

TensorFlow

NLP

Deep Learning

Education

Ph.D. in Computer Science or related field

Job description

Meta invites AI Research interns to join the Video Recommendations team on Facebook, focusing on end-to-end ML/NLP problems at the intersection of Product, ML, and Infra. Interns collaborate with Researchers and Software Engineers across start-to-finish challenges, framing practical questions into rigorous ML solutions.

The role spans 12 to 24 weeks with multiple start dates, offering exposure to cutting-edge research and real-world product impact on video content recommendations.