Research Scientist, Machine Learning

Meta•Sunnyvale, CA

1d•$122,000 - $181,000

About The Position

Meta is seeking a Research Scientist to join our Core Machine Learning Research team, where we advance the foundational AI and ML technologies that power Meta's family of products at scale. In this role, you will conduct original research in areas such as deep learning, representation learning, generative modeling, optimization, and large-scale model architectures. You will collaborate closely with researchers and engineers across the organization to translate novel findings into real-world impact, publish at top-tier venues, and help shape the direction of machine learning research at Meta.

Requirements

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 degree in Machine Learning, Artificial Intelligence, Computer Science, Statistics, Applied Mathematics, or a related technical field. Degree must be completed prior to joining Meta
Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment
2+ years of research experience in machine learning, including designing and implementing novel algorithms using deep learning frameworks such as PyTorch or TensorFlow
2+ years of experience with Python or C++ for research and systems development in machine learning contexts
Experience conducting experiments to validate research hypotheses and communicating findings through written papers, technical reports, or presentations

Nice To Haves

Demonstrated software engineering experience through open-source contributions, research internships, or widely adopted research implementations
Experience manipulating and analyzing large-scale, high-dimensional datasets for model training and evaluation
Research experience in one or more specialized areas including large language models, self-supervised learning, reinforcement learning, causal inference, graph neural networks, or ML systems and hardware-software co-design
Proven research contributions demonstrated by first-authored publications at leading venues such as NeurIPS, ICML, ICLR, AAAI, CVPR, ACL, or similar conferences

Responsibilities

Conduct original research in core machine learning areas including deep learning, representation learning, generative modeling, optimization, and large-scale model architectures
Design, implement, and evaluate novel ML algorithms and models using frameworks such as PyTorch, iterating based on experimental results and data-driven insights
Run controlled experiments to test research hypotheses, analyze outcomes, and make informed decisions in collaboration with research and engineering partners
Write clean, well-structured research code and contribute to shared codebases, ensuring reproducibility and maintainability of experiments
Produce and submit research findings to top-tier machine learning conferences and workshops such as NeurIPS, ICML, ICLR, or similar venues
Collaborate with cross-functional partners across research, engineering, and product teams to integrate research innovations into production systems at scale
Participate in code and design reviews, providing and incorporating technical feedback to improve research quality and implementation robustness
Build logging, monitoring, and evaluation pipelines to track model performance and detect regressions during research and deployment phases
Contribute to the health of the research community by participating in programs such as reading groups, research reviews, and onboarding support for incoming researchers