Your Fastest Path to a Career
in Machine Learning


Fellowship Program Focuses on
Real-world Experience

We give aspiring machine learning engineers the chance to hone their skills by building real-world applications. The number one qualification employers look for when hiring an ML engineering candidate is previous experience. Program highlights:

Build scalable machine learning models with agile software development methodology

Mentoring by experienced ML practitioners

Pair program with other fellows

Apply latest research in deep learning, reinforcement learning, generative adversarial networks

Full-time for three months

Fully remote with optional in-person collaboration

Fully remote ML program with interactive projects

Fellows from previous cohorts are now in data science roles at Uber Advanced Technologies Center, Facebook, Yelp, Google, Salesforce, Orange, and Ernst & Young. See a complete list of our past fellows.

Why do you need a Fellowship recommendation?

During the program, every fellow must submit a daily scrum update of their work and progress. These scrums will be recorded and later on reflected on your recommendation letters. This way, each fellow will be able to get detailed documentation and a letter. That being said, codes’ qualities, reading groups presentations, demo sessions performances, and blog contributions will also be reflected in the letter and reported to the partnering companies. 

Network of Past Fellows

The program addressed my desire to research the latest deep learning advancements and to interface with and deliver actual products to real clients. Not only did I learn a great deal about machine learning from the mentors, but also how to efficiently manage and deliver a product.

Stephanie Oh, Facebook

Fellowship.AI introduced me to real-world projects, which is a jump start when switching from an academic role to industry. What's more, you can meet a group of similar interesting fellows with passions and ideas, which might be even a bigger benefit in the long run.

Yuecheng Zhu, Google

Fellowship.AI provided a community of passionate machine learning practitioners and real world projects that helped solidify and deepen my knowledge, while at the same time instilling confidence in my ability to bring significant, measurable value to clients.

Alex Chao, Uber ATC

My Fellowship experience exposed me to the industrial applications of deep learning, paving way to kick start my career as a Data Scientist.  The externship offered to me in a leading crypto-currency trading company further enhanced my experience in various security aspects, scalability, response times of the models deployed. All of these experiences collectively helped me pursue a full-time career in one of the leading Financial Services company.

Sharath Kalkur, Mastercard

The Fellowship.AI program was the best way for me to transition into a career in data science. I was able to work on multiple commercial projects in a short period of time, as well as connect with others in the ML community. Through the following externship I gained experience abroad delivering large-scale projects to international clientele, and was placed in a role doing cutting-edge work in the industry afterwards.

Viv Pitter, Evolv Technologies

Enrolling in Fellowship.AI was one of the best professional decisions I've ever made.  It gave me a feel for how real projects with real constraints and challenges unfold beyond an academic data science setting. The immersive nature of the program helped me build perspective on the professional landscape, and build confidence in making the career leap from research to industry.

Luis Zertuche, Stitch fix

Hiring Partners & Employers

Aspiring data scientists that come from outside of computer science, have something to prove to themselves and to the world, and therefore work extra hard. I couldn’t be happier with the Fellows that we’ve hired at Onfido.

Mohan Mahadeva, onfido

I’m really impressed by everything the Fellowship.AI team is doing - after spending time on-site, we decided to hire one of the Fellows for our medical deep learning company.

Jeremy Howard,