Research Intern, Generative AI & World Modeling

Changing the world and user experiences through learned world knowledge is at the core of our team’s mission. We are seeking a Research Intern with a strong foundation in statistics and applied mathematics to work alongside a diverse group of researchers. In this role, you will conduct fundamental research that bridges rigorous mathematical theory with state-of-the-art applications in machine learning, computer vision, computer graphics, and physical AI.

What You’ll Do

• Fundamental Research: Leverage statistics, probability theory, and applied math to develop novel algorithms for machine learning (ML), computer vision (CV), and computer graphics (CG).
• Innovation & Prototyping: Translate core mathematical and statistical insights into scalable algorithms and open-source prototypes.
• Academic Impact: Publish groundbreaking work in top-tier machine learning, computer vision, and computer graphics conferences and journals (e.g., NeurIPS, ICML, CVPR, and SIGGRAPH).

Requirements:

• Ph.D. candidate with a strong background in statistics, probability, continuous optimization, linear algebra, or differential equations, with a passion for applying fundamental theory to real-world problems
• Proven hands-on experience with SOTA machine learning algorithms, especially with generative machine learning and/or fine-tuning of LLMs/LVMs, and familiarity with ML implementation environments and platforms such as PyTorch and/or TensorFlow.
• Deep knowledge and hands-on experience in computer vision and computer graphics are a plus.
• Strong programming skills in Python or C / C++ for Windows and/or Linux are required.
• Experience in working with open-source software frameworks is a plus
• Self-motivated, detail-oriented team player
• Good verbal and written communication skills

Duration of the job: 3-6 months

Futurewei Technologies, Inc. is proud to be an Equal Opportunity Employer.

All qualified applicants will receive consideration for employment without regard to race, color, gender, sexual orientation, gender identity or expression, religion, national origin, marital status, age, disability, veteran status, genetic information, or any other protected status under federal, state, and local laws.