Whether one likes it or not, America was built by immigrants, the wretched masses that the Statue of Liberty inscription asks to welcome with open arms. From Albert Einstein to Elon Musk, immigrants made America a great country, and now it looks like they are making America great again (MAGA, as the slogan goes), and this time in artificial intelligence. America’s edge isn’t just its innovation, it's the global brainpower who has been giving an edge to the country for centuries. And nothing makes that clearer than the news out of Meta’s new Superintelligence Lab: 11 top AI researchers hired, and every single one of them is an immigrant.
That’s right, not one US undergrad among them. These are elite engineers, model architects, and machine learning pioneers who began their academic journeys in India, China, South Africa, the UK, and Australia. They trained in America’s best labs, built some of the most advanced AI systems at OpenAI, DeepMind, and Anthropic, and now they’ve been snapped up by
Zuckerberg to build the next wave of intelligence. If you want to understand why the US leads the world in AI, you don’t need to look at GPUs or model benchmarks. Just look at the passports of the people writing the code.
Immigrants have long been the silent engine of Silicon Valley. From coding at Google to architecting cloud infrastructure at Microsoft, they form the backbone of America’s biggest tech empires. A significant number of these engineers hail from India, whose talent pipeline has become essential to the innovation output of the U.S. tech sector. They don’t just fill jobs, they define the direction of the industry. Now, as AI becomes the next great technological frontier, these same minds are shaping the models, algorithms, and safety protocols that will govern its future. Meta’s new superintelligence team is just the latest proof that without immigration, there is no AI revolution.
Top AI talent hired by Meta to power its superintelligence lab
Trapit Bansal
Background: Previously at OpenAI
Education:Master of Science (M.Sc. Integrated), Mathematics & Statistics, IIT Kanpur
Doctor of Philosophy (PhD), University of Massachusetts Amherst, USA
Profile:Bansal is recognized for his groundbreaking work in reinforcement learning applied to chain-of-thought reasoning, a technique that helps AI models improve logical step-by-step problem-solving. As a co-creator of the o-series models, he has set new standards in large language model performance and reliability. Bansal’s research is widely cited and has influenced both academic and industrial AI systems.
Shuchao Bi
Background: Previously at OpenAI
Education:Bachelor of Science (BS), Zhejiang University, China
Doctor of Philosophy (PhD), University of California, Berkeley, USA
Profile:Bi is a leader in multimodal AI, having co-developed the voice mode for GPT-4o and the o4-mini model. His expertise lies in integrating speech and text, enabling AI to understand and generate content across different formats. Bi’s work has been crucial in advancing conversational AI and making digital assistants more natural and accessible.
Huiwen Chang
Background: Previously at Google Research
Education:Bachelor of Science (BS), Tsinghua University, China
Doctor of Philosophy (PhD), Princeton University, USA
Profile:Chang is known for inventing the MaskIT and Muse architectures, which have become foundational in generative image models. She led the GPT-4o image generation team, driving innovations that allow AI to create high-quality, realistic images from text prompts. Her research bridges the gap between computer vision and creative AI applications.
Ji Lin
Background: Previously at OpenAI
Education:Bachelor of Engineering (BEng), Tsinghua University, China
Doctor of Philosophy (PhD), Massachusetts Institute of Technology (MIT), USA
Profile:Lin has played a key role in optimizing and scaling large language models, including GPT-4o and the o4 family. His work focuses on model efficiency and image generation, making state-of-the-art AI more accessible and cost-effective for real-world deployment. Lin’s contributions are highly regarded in both academia and industry.
Joel Pobar
Background: Previously at Anthropic & Meta
Education:Bachelor of Information Technology (Honours), Queensland University of Technology (QUT), Australia
Profile:Pobar is a veteran infrastructure specialist with over a decade of experience building scalable AI systems. He has contributed to major projects like HHVM, Hack, and PyTorch, which are widely used in the tech industry. Pobar’s expertise ensures that AI models run efficiently at scale, supporting rapid innovation and deployment.
Jack Rae
Background: Previously at Google DeepMind
Education:Bachelor of Science (BS), University of Bristol, UK
Master of Science (MS), Carnegie Mellon University (CMU), USA
Doctor of Philosophy (PhD), University College London (UCL), UK
Profile:Rae is a leading figure in large-scale language model research, having led pre-training for Gemini 2.5 and developed Google’s Gopher and Chinchilla models. His work has advanced the understanding of model scaling laws and data efficiency, shaping the next generation of AI systems.
Hongyu Ren
Background: Previously at OpenAI
Education:Bachelor of Science (BS), Peking University, China
Doctor of Philosophy (PhD), Stanford University, USA
Profile:Ren has contributed to the development and post-training of GPT-4o and the o1/3/4o-mini models, focusing on improving robustness and reliability. His research addresses key challenges in making AI models safer and more trustworthy for widespread use.
Johan Schalkwyk
Background: Previously at Google
Education:Bachelor of Science in Engineering (BS Meng), University of Pretoria, South Africa
Profile:Schalkwyk is a Google Fellow and a pioneer in speech recognition, having led the Maya team and contributed to the early development of Google’s Sesame project. His innovations have set industry standards in voice technology, powering products used by millions worldwide.
Pei Sun
Background: Previously at Google DeepMind
Education:Bachelor of Science (BS), Tsinghua University, China
Master of Science (MS), Carnegie Mellon University (CMU), USA
Profile:Sun specializes in post-training and reasoning for advanced AI models, including Gemini, and has developed perception systems for Waymo’s self-driving cars. His work bridges AI research and real-world applications, particularly in autonomous systems and robotics.
Jiahuai Yu
Background: Previously at OpenAI & Gemini
Education:Bachelor of Science (BS), University of Science and Technology of China (USTC), China
Doctor of Philosophy (PhD), University of Illinois Urbana-Champaign (UIUC), USA
Profile:Yu has made significant contributions to perception and multimodal AI, working on o3/4o-mini and GPT-4/4o. His research enables AI to interpret and generate information across text, images, and other modalities, expanding the possibilities of human-AI interaction.
Shengjia Zhao
Background: Previously at OpenAI
Education:Bachelor of Science (BS), Tsinghua University, China
Doctor of Philosophy (PhD), Stanford University, USA
Profile:Zhao is a co-creator of ChatGPT, GPT-4, and o4-mini, and has led research on data synthesis and AI safety. His work has had a direct impact on the reliability and ethical deployment of generative AI, making him a respected voice in the field.
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