Meta is seeking a Research Scientist to join our Instagram Core ML team. This team is an applied research organization focused on improving the quality of IG recommendation models through AI. Advances in AI are key to our mission, spanning some of the most pressing research challenges of our generation across such areas as artificial intelligence, machine learning, and optimization, with a particular focus on recommendation systems, reinforcement learning, generative models, and natural language processing. The ideal candidate will have a solid research background in core ML in at least one of theory, algorithm, and systems, with a keen interest in solving the product problem via customized principled solutions. Research backgrounds in recommendation systems or related research areas such as information retrieval can be a bonus.

Responsibilities

Develop and evaluate scalable specific deep learning models for recommendation systems.
Develop and evaluate sequence modeling algorithms and systems.
Solve the product bottleneck problems via customized ML solution.
Collaborate with scientists on novel research in generative modeling, complex systems, and reinforcement learning.
Apply knowledge of relevant research domains and coding skills to platform and framework development projects.
Adapt machine learning and neural network algorithms to best exploit modern parallel environments (e.g. distributed clusters, GPUs, TPUs, etc.).

Minimum Qualifications

Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta.
Currently has, or is in the process of obtaining a PhD in the field of Computer Science, Artificial intelligence or equivalent practical experience. Degree must be completed prior to joining Meta.
Experience developing machine learning algorithms or machine learning infrastructure in Python and PyTorch and Slurm.
Experience in deep learning: supervised, semi-supervised, self-supervised learning and/or generative modeling.
Research experience in generative AI (language, image, videos).
Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment.

Preferred Qualifications

Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as publications at leading workshops, journals or conferences such as NeurIPS, ICML, ICLR, KDD/ICDM, RecSys, CVPR/ICCV, etc.
Demonstrated research and software engineering experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub).
Research background in Recommendation systems or information retrieval
Experience working and communicating cross functionally in a team environment.
Experience solving complex problems and comparing alternative solutions, tradeoffs, and diverse points of view to determine a path forward.

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