- Initiate and lead efforts towards ambitious research goals, while identifying intermediate milestones to reach and gathering insights step by step.
- Conduct innovative research on deep-learning algorithms and models that can eventually be deployed into Meta’s recommendation products, meeting industry-level requirements on efficiency, scalability, and stability.
- Collaborate with researchers and cross-functional partners including communicating research plans, progress, and results. Document findings and share learnings internally.
- Publish research results and contribute to research that can be applied to Meta product development.
- Currently has or is in the process of obtaining a Ph.D. degree in Computer Science or a related field.
- Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment.
- Familiarity with machine learning and common deep learning architectures.
- Experience with Python, especially machine learning libraries such as Pytorch and TensorFlow.
- Intent to return to degree-program after the completion of the internship/co-op.
- Proven track record of solid research achievements as demonstrated by grants, fellowships, patents, as well as publications at leading AI conferences such as NeurIPS, ICML, ICLR, KDD, ACL, EMNLP, etc.
- Past experience in conducting research on recommendation system, graph representation learning.
- Demonstrated software development experience via tech internships, work experience, coding competitions, or widely used contributions in open source machine-learning repositories.
- Experience working and communicating cross functionally in a fast-paced team environment. Ideal candidates should have the ability to quickly understand and identify the research opportunities behind real-world applications, select the appropriate ML methods to explore, and proactively drive the iterations based on clear analysis of the current results.
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