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 researchersCurrently 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 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 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 conferencesMeta builds technologies that help people connect, find communities, and grow businesses.