Tips for getting hired as AI research engineer

Figure source

◊Join Kaggle competition, and develop machine learning algorithms
[Ex] https://www.kaggle.com/jacky10312003

There are many Kaggle competition topics coming out from time to time. The dataset is well-prepared. Find some time and practice real-world prediction problems.

◊Join AI hackathon, and keep the finished project result
[Ex] https://chuangtc.com/tmu_hackathon2018/

Hackathon is organized mostly for students or startups during weekend. Form a team or just go straight and find partners in a hackathon. You will learn how to squeeze your time and finish something in a short period of time. The time constraints and pressure will push you learn more after the hackathon. You will also meet some professionals who can effectively use the short period of time and squeeze out some good results.

◊Use Jupyter Notebook to practice data science with statistics and machine learning algorithms
[Ex] https://github.com/chuangtc/tmu_hackathon2018/tree/master/data_analysis

Jupyter Notebook is really a good debugging tool for data scientists. It’s easier to print out middle results or visualize data.

◊Demo Personal independent AI project, and put the source code on Github.
[Ex] https://chuangtc.com/ParallelComputing/OpenCV_Nvidia_CUDA_Setup.php

For what you are working on, try to put the source code on Github. It will let your future coworkers or future boss know what you have done before. During the process, you will learn how to organize a project folder structure. You will learn how to remove redundant code and make it clean. You will also learn how to make it readable by others.

◊Write down your learning experience for AI/ML on blogger(Ex. Medium/Wordpress/Blogger/Linkedin).
[Ex] https://www.topbots.com/

The technology of AI/ML/Data science evolves very quickly. Write down what you learned. Your experience might inspire other people. If someone noticed that there is a better way. They might give you feedback, and it’s going to benefit yourself most.

◊Earn AI/ML related education degree. It could be Bachelor, Master, or PhD degree.

MIT has announced a $1 billion plan to create a new college for AI in late 2018. More and more schools see the importance of AI education. The AI related knowledge came from Computer Engineering/Computer Science/ Applied Mathematics/ Statistics. If you are really into AI, try to apply for college or graduate school in any of those disciplines.

◊Have some AI/ML research paper published.

If you are at graduate school, try to make your work get published in conference. At least it got judged by professionals. It also showed that your work is valued among AI/ML researchers.

◊Set up personal website, or use github.io host your AI portfolio.
[Ex] Some example websites for AI/ML portfolio

Jason TC Chuang
https://chuangtc.com/
Hammad A Usmani
https://hammad93.github.io/

In the end, you can organize what you did, and put together on a website. When you have an AI/ML interview, you can happily give out an URL link to your interviewer. It’s going to increase your chance to move on to the next step of interview.


Originally published at ai4quantblog.com on November 6, 2018. Edited on January 14, 2019.