AI Research Engineer
Meta

Meta is seeking a Research Engineer to join our Fundamental AI Research (FAIR) Team, a research organization focused on making significant progress in 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, computational statistics, and applied mathematics, particularly including areas such as deep learning, generative models, reinforcement learning, computer perception, natural language processing. The ideal candidate will have a keen interest in producing new science to understand intelligence and technology to make computers more intelligent.

AI Research Engineer Responsibilities:

• Write clean machine learning code in Python.
• Engineer, design, implement, and improve Machine Learning systems and tools for enabling research.
• Collaborate on research projects within a distributed team to advance the science and technology of intelligent machines.

Minimum Qualifications:

• Experience programming in Python or other related language.
• 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.
• Experience using PyTorch or similar deep learning libraries.
• Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment.

Preferred Qualifications:

• Currently has, or is in the process of obtaining a Master's degree in Computer Science, Machine Learning, Data Science, relevant technical field, or equivalent practical experience.
• Co-authored publications at peer-reviewed conferences (e.g. NeurIPS, ICLR, CVPR or similar).
• 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.
• Demonstrated research and software engineering experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub).