Research Scientist Intern, AI Compilers (PhD) - Meta

Meta was built to help people connect and share, and over the last decade our tools have played a critical part in changing how people around the world communicate with one another. With over a billion people using the service and more than fifty offices around the globe, a career at Meta offers countless ways to make an impact in a fast growing organization.We are committed to advancing the field of artificial intelligence by making fundamental advances in technologies to help interact with and understand our world. We are seeking individuals passionate in areas such as deep learning, natural language processing, machine learning, reinforcement learning, computational statistics, applied mathematics, compiler and programming languages. Our interns have an opportunity to make core algorithmic advances and apply their ideas at an unprecedented scale.Our internships are twelve (12) to twenty-four (24) weeks long and we have various start dates throughout the year.

RESPONSIBILITIES

Research Scientist Intern, AI Compilers (PhD) Responsibilities:

• Perform state of the art research to advance the science and technology of Machine Learning and Artificial Intelligence.
• Contribute research that leads to innovations in: optimising programs by enhancing compilers with AI and LLMs.
• Collaborate with researchers and cross-functional partners including communicating research plans, progress, and results.
• Publish research results and contribute to research that can be applied to Meta product development.

MINIMUM QUALIFICATIONS

Minimum Qualifications:

• Currently has or is in the process of obtaining a Ph.D. degree in Machine Learning, Systems, Artificial Intelligence, or relevant technical field.
• Must obtain work authorization in country of employment at the time of hire and maintain ongoing work authorization during employment.
• Experience with Python, C++, C, Lua or other related language.

PREFERRED QUALIFICATIONS

Preferred Qualifications:

• Intent to return to degree program after the completion of the internship/co-op.
• Proven track record of achieving significant results as demonstrated by first-authored publications at leading workshops or conferences such as NeurIPS, ICML, ICLR, MLSys, ISCA, ASPLOS, CGO, PLDI, PACT, HPCA, MICRO, or similar.
• Publications or experience in systems, computer architectures, compiler and programming languages, machine learning, AI, optimization, computer science, statistics, applied mathematics, or data science.
• Experience solving analytical problems using quantitative approaches.
• Ability to manipulate and analyze complex, large scale, high-dimensionality data from varying sources.
• Experience in utilizing theoretical and empirical research to solve problems.
• Experience building systems based on machine learning and/or deep learning methods.
• Demonstrated software engineer experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub).
• Experience working and communicating cross functionally in a team environment.