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Meta · 4 months ago

Research Scientist Intern, AI Core Machine Learning (PhD)

New York, NY

Internship

Onsite

Intern

Meta is a technology company that connects people and fosters communication globally. They are seeking Research Interns to advance artificial intelligence and machine learning technologies, focusing on personalized ads and collaboration with researchers and engineers.

Computer Software

Comp. & Benefits

No H1B

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

Qualification

Machine LearningArtificial IntelligenceDeep LearningPythonPytorchTensorflowC++Research ExperienceData AnalysisTeam CollaborationProblem Solving

Required

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

Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment

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

Preferred

Intent to return to degree program after the completion of the internship/co-op

Proven track record of achieving significant research results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences such as NeurIPS, ICML, ICLR, AAAI, KDD, IJCAI, CVPR, ICCV, ACL, NAACL, ICASSP, or similar

Demonstrated software engineer experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub)

Demonstrated experience and self-driven motivation in solving analytical problems using quantitative approaches

Experience manipulating and analyzing complex, high-volume, high-dimensionality data from varying sources for large-scale training

Experience working and communicating cross functionally in a team environment