Research Scientist ML Training Infra

Meta is seeking a Research Scientist to join our Ads Training Performance Team within the Monetization organization, a group focused on making a significant impact in AI by building next generation ML infra. We are responsible for the infrastructure that trains models that power the ranking and recommendation system for ads served in Meta. The ideal candidate will have a keen interest in producing new ML Infra solutions to improve model training including training performance through GPU optimizations.

Research Scientist, ML Training Infra Responsibilities:

• Develop highly scalable and performant ML Infra.
• Collaborate with Research Scientists on novel research in modeling and complex systems.
• Apply knowledge of relevant research domains and coding skills to platform and framework development projects.
• Mentor other team members. Arbitrate in cases of technical disagreement among team members. Play a significant role to have a healthy cross-functional collaboration.
  

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 Machine Learning, Artificial Intelligence, Computer Science, Information or Multimedia Retrieval, Reinforcement Learning, Mathematics, or related technical field, or equivalent practical experience. Degree must be completed prior to joining Meta.
• Experience with research and building infra for Machine Learning.
• Experience with Python, C++, Java, or other related languages.
• Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment.
  

Preferred Qualifications:

• Experience solving analytical problems using quantitative approaches.
• Experience manipulating and analyzing complex, high-volume, high-dimensionality data from varying sources.
• Experience with developing Machine Learning Infra at scale from inception to business impact.
• 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 (e.g., NeurIPS, CVPR, ICML, ICLR, ICCV, and ACL) or similar.
• Demonstrated research and software engineering experience via an internship, work experience, coding competitions, or widely used contributions in open-source repositories (e.g. GitHub).
• Experience solving complex problems and comparing alternative solutions, tradeoffs, and diverse points of view to determine a path forward.
• Experience working and communicating cross functionally in a team environment.