Research Scientist, AI Recommendation Systems (PhD) - Meta

At Meta, we use machine learning across a diverse set of applications to help people discover better content more quickly, and to connect with the things that matter most to them.Modern Recommendation System organization focuses on developing efficient foundational models as a platform to enable differentiated and delightful user experiences across Meta products. We are seeking a talented AI Research Scientist with experience in recommendation system, language models and general AI to join the team

RESPONSIBILITIES

Research Scientist, AI Recommendation Systems (PhD) Responsibilities:

• Develop algorithms based on state-of-the-art machine learning and neural network methodologies.
• Define, build, and benchmark the efficient foundation models for recommendation system Conduct research towards long-term ambitious research goals while identifying intermediate milestones.
• Conduct research to advance the science and technology of recommendation systems, large language models and generative AI modeling.
• Work with engineering teams to ship state-of-the-art models to product.

MINIMUM QUALIFICATIONS

Minimum Qualifications:

• Currently has, or is in the process of obtaining, a PhD in Machine Learning, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta.
• Knowledge in Python, Java, C++ or PHP.
• Research and/or work experience in machine learning, NLP, recommendation systems, pattern recognition, signal processing, data mining, artificial intelligence, information retrieval or computer vision.
• Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment.
• 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.

PREFERRED QUALIFICATIONS

Preferred Qualifications:

• Demonstrated software engineer experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub)
• Proven track record of achieving results as demonstrated by grants, fellowships, patents, as well as first-authored publications at workshops or conferences such as ICML, NIPS, KDD or similar.
• Experience working and communicating cross-functionally in a team environment.