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20 Best ML Experts

best ml experts - 20 Best ML Experts

Machine learning has changed nearly every corner of technology, and behind it stands a diverse, global community.

From open-source pioneers and well-known educators to startup founders still writing code and competition legends breaking records, today’s leading ML experts are pushing AI forward with both brains and heart. Below is an updated and ranked list of the most active and significant machine learning professionals in the world, selected for their influence across open-source tools, research, industry innovation, and real-world applications:

  1. Jeremy Howard
  2. Tianqi Chen
  3. François Chollet
  4. Marios Michailidis
  5. Soumith Chintala
  6. Moustapha Cissé
  7. Thomas Wolf
  8. Andrej Karpathy
  9. Oriol Vinyals
  10. William Falcon
  11. Abhishek Thakur
  12. Chip Huyen
  13. Sebastian Raschka
  14. Sandip Das
  15. Gilberto Titericz Jr.
  16. Andrew Ng
  17. Yann LeCun
  18. Fei-Fei Li
  19. Jeff Dean
  20. Anima Anandkumar

Now, let’s look at their qualifications and achievements:

Jeremy Howard

YouTube Video

The End of Finetuning.

Nationality: Australian / American

Jeremy is a prominent data scientist and educator who co-founded fast.ai, an organization making deep learning more accessible, and more recently Answer.AI, an AI research lab.

He was President and Chief Scientist of Kaggle, where he helped shape the competitive data science community. In recent years, Howard has focused on teaching practical AI—his fast.ai courses and open-source library (Fastai) have trained thousands of engineers. A four-time Kaggle competition winner earlier in his career, Howard continues to influence ML through research, coding, and mentorship.

Tianqi Chen

Nationality: Chinese

Tianqi is an AI researcher and engineer known for creating essential tools in the ML ecosystem.

He is the original creator of XGBoost, the gradient boosting library that became a favorite winning method for tabular data competitions and industry use. He also co-created Apache MXNet and Apache TVM, the automated deep learning compiler used to optimize models on various hardware. Chen co-founded OctoML in 2019 to commercialize the TVM technology; the company (later renamed OctoAI) was acquired by NVIDIA in 2024 – he’s now a Distinguished Engineer at NVIDIA and an assistant professor at CMU.

For bridging algorithmic innovation with systems engineering (and open-sourcing it all), Tianqi Chen is globally acclaimed in machine learning circles.

Francois Chollet

Francois Chollet - 20 Best ML Experts

Nationality: French

François is the creator of Keras, the high-level deep learning API released in 2015 that has become a standard for building neural networks.

A former Google AI researcher, Chollet’s work spans computer vision and reasoning; he authored the Xception CNN architecture and the book Deep Learning with Python, with over 100k copies sold. In 2019 he introduced the ARC challenge for AI generalization, and in 2024 he launched a $1M ARC Prize competition. He left Google in late 2024 and, in 2025, co-founded Ndea, a new AI research lab.

Named one of TIME’s 100 most influential people in AI in 2024, Chollet is known for significant open-source contributions and his writing on ML.

Marios Michailidis

Nationality: Greek

Marios is a 2× Kaggle Grandmaster who was ranked #1 worldwide in competitions at his peak.

He has 40+ gold medals on Kaggle and has used that experience in industry as a Senior Data Scientist at H2O.ai. Marios co-created StackNet, an open-source stacking framework for model ensembling, and has been an influential figure in the competitive ML community. He holds a PhD in Machine Learning and has shared his expertise through many forums and talks.

By combining elite competition skill with real-world ML product development (including contributing to H2O’s AutoML), Michailidis represents the gold standard in applied machine learning excellence.

Soumith Chintala

Soumith Chintala - 20 Best ML Experts

Nationality: Indian

Soumith co-founded and leads development of PyTorch, one of the most popular open-source deep learning frameworks.

For over a decade as an AI engineering lead at Meta (Facebook), he drove PyTorch’s growth from an academic project into a tool powering most of the world’s AI research; in November 2025 he left Meta to become CTO of Thinking Machines Lab. Chintala has a strong research background (co-authoring well-cited GAN papers like DCGAN) and actively maintains open-source ML libraries.

His work in democratizing deep learning through PyTorch – known for its flexibility and performance – has made an extraordinary real-world impact.

Moustapha Cisse

Nationality: Senegalese

Moustapha is a leading AI researcher and a champion of AI in Africa. He was the founding Head of Google’s first AI research center in Africa (Accra, Ghana), directing research on foundational ML and its societal applications.

Cissé also co-founded and directs the African Masters in Machine Intelligence (AMMI), training the continent’s next generation of AI talent. With a PhD in machine learning, he has contributed to fairness and accountability in AI, striving to “solve complex societal challenges” through ML.

Now an entrepreneur (founder and CEO of digital-health startup Kera Health Platforms), Cissé’s blend of technical expertise and impact-driven leadership makes him an inspiration and globally recognized ML expert.

Thomas Wolf

Thomas Wolf - 20 Best ML Experts

Nationality: French

Thomas is co-founder and Chief Science Officer of Hugging Face, the startup behind Transformers – the open-source library that reshaped NLP by bringing advanced models to all.

He pioneered the “community hub” model for ML, leading Hugging Face to provide thousands of pretrained models and datasets. Wolf’s work in democratizing transformer architectures (BERT, GPT, etc.) has catalyzed innovation in natural language processing. Under his leadership, Hugging Face has become synonymous with open-source AI, letting researchers and developers worldwide build on the latest advances in NLP.

Andrej Karpathy

Neural networks are just glorified matrix multiplication.

Nationality: Slovakian / Canadian

Andrej is a renowned AI researcher and engineer who has bridged academia and industry.

As Director of AI at Tesla (2017–2022), he led the computer vision team developing the Autopilot self-driving system. Earlier, Karpathy was a founding member of OpenAI and authored influential deep learning papers (he was co-author of the pioneering ImageNet classification work as a student). He’s known for his teaching—Karpathy’s blog and Stanford course CS231n (Convolutional Nets) inspired a generation of developers. In 2023 he rejoined OpenAI to work on GPT, then left in February 2024 to launch the AI-education startup Eureka Labs; in May 2026 he joined Anthropic to lead pretraining research.

His ability to deliver real-world AI systems (at Tesla) and communicate ideas broadly makes him a key figure in ML.

Oriol Vinyals

Nationality: Spanish

Oriol is a Principal Research Scientist at DeepMind and one of the world’s top minds in deep learning.

A former International Olympiad in Informatics gold medalist, he has applied his talent to breakthrough AI research. Vinyals co-authored the seminal sequence-to-sequence learning paper for neural machine translation and later led DeepMind’s efforts in mastering complex games. He led AlphaStar, the first AI to defeat top professionals in StarCraft II, opening new ground in reinforcement learning.

Recognized as “one of the foremost minds in AI research”, Vinyals now leads DeepMind’s Gemini project (next-gen AI) and continues to push the envelope in multi-agent learning and AI generalization.

William Falcon

William Falcon - 20 Best ML Experts

Nationality: Puerto Rican / American

William is the creator of PyTorch Lightning, an open-source framework that has simplified how researchers train high-performance deep learning models.

He founded Lightning AI (formerly Grid.ai) to further build tools for scalable AI engineering. Falcon developed PyTorch Lightning during his PhD at NYU (advised by Yann LeCun), abstracting the boilerplate of PyTorch and enabling rapid experimentation for thousands of researchers. Under his leadership, Lightning AI has grown into a platform for simplifying ML model building and deployment.

Falcon’s blend of academic insight and startup execution, all while actively coding (he was Lightning’s original core developer), makes him a notable figure in ML engineering.

Abhishek Thakur

Nationality: Indian

Abhishek is the world’s first Quadruple Kaggle Grandmaster, achieving top rankings in competitions, notebooks, discussions, and datasets.

A applied ML expert, he has won multiple international data science competitions. Thakur served as a Machine Learning Engineer at Hugging Face, where he built AutoNLP tools. He’s also known for educating the community—authoring the popular book Approaching (Almost) Any Machine Learning Problem and sharing knowledge through blogs and YouTube.

His combination of competition success and practical tooling in NLP (e.g. Hugging Face’s AutoTrain) demonstrates a rare, well-rounded excellence in ML.

Chip Huyen

Chip Huyen - 20 Best ML Experts

Nationality: Vietnamese

Chip is a leading voice in machine learning systems and MLOps. As co-founder of Claypot AI, she built a platform for real-time ML; the company was acquired by Voltron Data in 2024, where she went on to serve as VP of AI & Open Source.

Huyen has worked on ML infrastructure at Snorkel AI, NVIDIA, and Netflix, giving her broad industry expertise. She is also an educator: teaching “Machine Learning Systems Design” at Stanford, which led to her bestselling 2022 book Designing Machine Learning Systems. Through her blog and speaking, Chip Huyen advocates for practical, efficient ML deployment.

Her contributions, spanning code, writings, and startup innovation, have made her a leading expert on bringing advanced ML from research to production.

Sebastian Raschka

Nationality: German

Sebastian is an open-source pioneer and educator in machine learning. He created mlxtend, a Python library of ML extensions, and has contributed to scikit-learn, helping to shape the tools many practitioners use.

Raschka is the author of the bestselling book Python Machine Learning; he spent several years as a lead AI educator at Lightning AI and now focuses on his own AI research and educational content. A PhD in deep learning, Raschka has published influential research but is equally known for translating complex concepts into intuitive code examples.

His commitment to open science (sharing code, blogs, and lectures) and his hands-on development of widely adopted ML software mark him as a top global ML expert.

Sandip Das

Nationality: Indian

Sandip is a Senior Cloud, DevOps, MLOps & ML Platform Engineer, recognized as a LinkedIn “Top Voice” and AWS Container Hero, who combines substantial cloud and DevOps expertise with a clear emphasis on MLOps and AI/ML education.

His article “Basic AI & ML Concepts Explained” demystifies fundamentals like AI, ML, ML models, and training paradigms—covering supervised, unsupervised, reinforcement, and semi‑supervised learning. As an educator and mentor, he bridges the gap between complex machine learning and real‑world application, helping learners grasp foundational concepts before getting into MLOps.

Through his content and hands‑on guidance, Sandip ensures that professionals are well‑prepared to confidently build, deploy, and manage ML workflows.

Gilberto Titericz Jr.

Nationality: Brazilian

Gilberto “Giba” is a legendary Kaggle Grandmaster from Brazil who at one point held the most gold medals on Kaggle (59) – a record-breaking achievement.

He was also ranked #1 globally in Kaggle competitions, proving his dominance in diverse ML challenges. Giba transitioned his expertise to industry as a Senior Data Scientist at NVIDIA, where he works on GPU-accelerated ML (RAPIDS). With an electrical engineering background, he approaches problems with both theoretical rigor and practical savvy.

His continued competition success, combined with developing advanced ML solutions at NVIDIA, puts Titericz among the world’s top practical ML experts.

Andrew Ng

Nationality: British

Andrew has influenced modern ML primarily through education and applied AI building blocks. He is Founder of DeepLearning.AI and Founder & CEO of Landing AI, and he is listed as a Managing General Partner at AI Fund.

At Stanford, he is an Adjunct Professor, and his work has consistently focused on making ML practical for engineers and teams shipping production systems. If you want an expert entry that leans into systems, training, and real-world adoption rather than a single open-source library, Ng fits cleanly into this list.

Yann LeCun

Nationality: French / American

Yann is a Turing Award laureate and one of the founding figures of modern deep learning.

Often called a “godfather of AI”, he developed convolutional neural networks (CNNs) in the late 1980s, the architecture now behind most computer vision systems, and built the LeNet model that read handwritten checks at scale. In 2013 he founded FAIR, Meta’s fundamental AI research lab, and served as the company’s Chief AI Scientist for more than a decade while remaining a professor at New York University. He shared the 2018 Turing Award with Yoshua Bengio and Geoffrey Hinton.

In late 2025 he left Meta to launch AMI Labs (Advanced Machine Intelligence), a startup pursuing “world models” that raised over $1 billion in early 2026, and he remains one of the field’s most outspoken voices on the direction AI should take.

Fei-Fei Li

Nationality: Chinese / American

Fei-Fei is a Stanford professor whose work helped set off the deep learning era and who is now building “spatial intelligence” AI.

She created ImageNet, the large-scale image dataset and competition that triggered the modern breakthrough in computer vision and neural networks. She co-directs the Stanford Institute for Human-Centered AI (HAI), previously served as Chief Scientist of AI/ML at Google Cloud, and wrote the memoir The Worlds I See. In 2024 she co-founded World Labs to build large world models.

World Labs raised about $1 billion in early 2026 and shipped Marble, a system that generates persistent 3D worlds from images or text, putting Li at the front of the shift from flat images to spatial AI.

Jeff Dean

Nationality: American

Jeff is Google’s Chief Scientist and the engineer behind much of the infrastructure that modern machine learning runs on.

He co-founded Google Brain, co-created TensorFlow, and built foundational large-scale systems such as MapReduce, Bigtable, and Spanner. After Google Brain merged with DeepMind in 2023, he became Chief Scientist of Google DeepMind and Google Research, helping steer the Gemini model program.

With a career spanning search infrastructure to deep learning at planetary scale, Dean is one of the most influential systems engineers in AI.

Anima Anandkumar

Nationality: Indian / American

Anima is a Caltech professor known for bringing machine learning to scientific computing.

As the Bren Professor of Computing at Caltech, she invented Neural Operators, a class of models that learn the physics behind phenomena like fluid dynamics and weather, and co-led FourCastNet, one of the first AI models for high-resolution global weather forecasting. She previously spent years as Senior Director of AI Research at NVIDIA and as a principal scientist at AWS before returning to academia full-time in 2023. Her earlier research pioneered tensor methods for learning latent-variable models.

By pointing ML at physics and the natural sciences, Anandkumar has helped open up the fast-growing area often called “AI for science”.

Wrap Up

These experts represent exceptional talent, making them extremely challenging to headhunt. However, there are thousands of other highly skilled IT professionals available to hire with our help. Contact us, and we will be happy to discuss your hiring needs.

Note: We’ve dedicated significant time and effort to creating and verifying this curated list of top talent. However, if you believe a correction or addition is needed, feel free to reach out. We’ll gladly review and update the page.

Frequently Asked Questions

What is the cost of hiring an ML developer?

ML developers in the United States typically earn $130,000 to $185,000 per year. Hourly contract rates range from $70 to $150 depending on specialization and project complexity. Rates in Eastern Europe and Latin America are generally more competitive.

What experience should I look for in an ML expert?

Look for strong skills in Python, TensorFlow or PyTorch, data preprocessing, and model deployment. Experience with cloud platforms (AWS, Azure, GCP) and domain knowledge relevant to your industry is also valuable.

Is it hard to find ML programmers?

Yes, skilled ML engineers are in high demand and the talent pool is smaller compared to general software developers. Competition from tech companies and startups makes hiring experienced professionals challenging. EchoGlobal helps companies hire remote ML engineers without the usual sourcing overhead.

Will AI replace ML developers?

AI tools are automating parts of the ML workflow, such as data labeling or model selection, but they do not replace ML developers. Human expertise is still required to define problems, interpret results, ensure ethical use, and align solutions with business needs.

What companies use machine learning?

Machine learning is used by companies such as Google, Amazon, Netflix, Tesla, and JPMorgan Chase, along with thousands of startups applying ML to recommendations, fraud detection, computer vision, and forecasting.

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