This told essay is based on a conversation with Rahul Kasanagottu, a 32-year-old Austin-based customer engineer at Google who specializes in AI and machine learning. His identity and employment have been confirmed by Business Insider. The following has been edited for length and clarity.
For several years, I worked in a customer success role at Google, but when the generative AI train came along, I knew I wanted to be a part of it.
During critical periods in technology, many people enter technology to make money. I think more people should be thinking about leveraging AI to influence how others use AI. That’s what I wanted to do.
My daughter was born in April 2023, and the AI boom was around that time. Since Google offers generous parental leave, I thought it would be a good opportunity to spend time with my daughter and start reading books about AI.
Paternity leave definitely helped me start my journey, but it took me about two and a half years, read 11 books, and watched hours of videos before I landed a job on the AI team. I interviewed for 4-5 different roles and 6 months ago moved from Senior Technical Account Manager to Google Cloud Customer Engineer specializing in AI and Machine Learning. In this role, you will create demos and show customers how to use Google’s AI products.
I am still continuing to improve my skills. Products are changing daily. Today I’m working with one type of customer, and tomorrow I might be working with a completely different customer with completely different needs. The learning curve is continuous.
Here are 11 books and courses that helped me improve my skills.
textbook:
Other books:
- Genesis by Henry Kissinger, Craig Mundy, and Eric Schmidt
Courses and YouTube Channel:
book
The two books I finished reading were “Designing Machine Learning Systems” and “Generative AI on AWS.” The latter has an accompanying course on deep learning, which was very important in my early learning.
Chip Fuen’s two books were my favorites. He explained things in a very approachable way and expanded my understanding of how organizations use and implement AI. At first, it was difficult to understand the difference between the research side and the application side of AI. These books helped me realize that my interest lies in applied AI.
“Power and Prediction” was also a favorite. Explain how technology needs to scale economically to bring about change. For example, not every home will be electrified today, even though light bulbs still cost thousands of dollars. These books talk about AI in similar terms.
“Genesis” also stood out. We talk about the future of AI and the challenges it brings.
Andrew Ng’s course was also really helpful. He is a great teacher and the founder of Google Brain.
Google’s culture also helped. Without the support of my manager and teammates, I would not have been able to find time for personal growth. I had to prioritize work and personal studies while caring for my newborn daughter. My wife also had to sacrifice a lot of time for me to work on my job.
solo project
Books typically do not come with assignments, but courses include many practical exercises. Over time, I realized that was the missing piece on my resume. The need to create demos and perform hands-on projects has made it difficult to convince recruiters that I can do the job.
I realized that I needed to do the project myself, and AI tools were very helpful for that.
For others who want to transition, I think you need to keep working hard. Connecting the dots in complex problems takes time, and you may have to read the same material over and over again to fully understand the concept.
Many people, including myself, who are interested in AI are in a hurry to get a job in AI in six months. However, many machine learning concepts take time to understand. Therefore, persistence is required.
Working in an AI role? We’d love to hear from you. Contact the reporter via email: aaltchek@insider.com or via the secure messaging app Signal aalt.19.
