Research Scientist Intern, Gen AI Large Language Models (LLM) (PhD)
Meta

Job Info

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, computer vision, audio and speech processing, natural language processing, machine learning, reinforcement learning, computational statistics, and applied mathematics. 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.

Research Scientist Intern, Gen AI Large Language Models (LLM) (PhD) Responsibilities:

• Perform research to advance the science and technology of large language models and AI.
• Experimenting LLM on large-scale (multimodal/multi-application) data. Improve the efficiency, scalability, and performance of LLM systems, optimizing for real-world applications.
• Collaborate with researchers and cross-functional teams, sharing research plans, progress, and findings.
• Contribute to Meta's LLM-focused research and publish results that can impact Meta's products and services.

Minimum Qualifications:

• Currently pursuing or in the process of obtaining a Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, NLP, CV, or a related technical field.
• Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization throughout the internship.
• Experience with Python, C++, or related programming languages.
• Proficiency in deep learning frameworks such as PyTorch or TensorFlow.
• Experience with developing and training LLMs, deep learning, or machine learning models on large-scale datasets.

Preferred Qualifications:

• Intent to return to the degree program after completing the internship/co-op.
• Proven track record of significant research contributions, as demonstrated by grants, fellowships, patents, or publications at top conferences such as ACL, NAACL, EMNLP, NeurIPS, ICLR, ICML, AAAI, CVPR, ECCV, ICCV, KDD, IJCAI, or similar.
• Hands-on experience with LLMs, including the latest advancements in text-only input and multimodal inputs for LLMs.
• Expertise in training and optimizing large neural networks, particularly in the context of LLM applications.
• Experience with the development and deployment of AI platforms that leverage LLMs, including those involving large-scale data management and GPU-accelerated compute.
• Demonstrated software engineering expertise through internships, work experience, coding competitions, or contributions to open-source projects (e.g., GitHub).
• Strong cross-functional communication skills and a collaborative mindset.

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