How an Indian engineer built an AI career in Silicon Valley

ForRakesh Utekar, the person who had the biggest influence on his AI career was someone he had never even met in person – Andrew Ng, managing general partner at AI Fund

Widely regarded as one of the most influential figures in AI, Ng has helped millions of people worldwide enter the field through his online courses

Years later, Utekar is now working alongside him

“I actually learned machine learning from him back in India through Coursera,” he says. “Working with him and at AI Fund was like a dream come true.”

A casual trip to San Francisco turned into a turning point for his tech career

It started long before Coursera

Growing up in India, using a computer often meant going to local cyber cafés – think shops where you can rent a computer to play games and browse the internet by the hour

He went with friends, but his attention rarely left the machines. Each visit pulled him deeper into understanding how computers worked and what they were capable of

When his parents bought him a laptop, he spent even more time experimenting with computers.He became obsessed with them

“Since then, I’ve always wanted to do something in tech,” he says

Soon, he went on to earn a Bachelor of Technology in Computer Engineering from the University of Mumbai, and it was there that he came across Ng’s Coursera course. By the time he graduated, he was already building

Utekar says showing up at the right place at the right time opened unexpected doors in his AI career

After graduation, he joined Stash RTC as a machine learning intern, his first taste of applying what he’d learned in the real world. “I worked on chatbots, text-to-speech models, and speech-to-text models,” he says. 

That experience pushed Utekar to set his sights on a master’s degree in the US, applying to several universities with a focus on machine learning

But one stood out

“Of the universities I considered, Stevens was the only one that offered a master’s specifically in machine learning, but I applied a little late and didn’t get in,” he says. 

“I got accepted to Seattle University for a Master of Computer Science with a specialisation in data science, which was perfect for me. At the time, none of the other universities I was considering offered computer science and data science together.”

At Seattle University, he threw himself into the programme – tackling rigorous coursework and hands-on projects that sharpened both his technical skills and analytical thinking. It gave him the structure to approach complex problems with more clarity and confidence

Utekar graduated in 2024 from Seattle University with a Master of Computer Science, specialising in Data Science

When showing up changed everything

Utekar graduated in June 2024 and walked straight into a tough job market. Roles were scarce and competition was fierce

He spent weeks applying and waiting. Nothing clicked

Then he took a trip to San Francisco. The visit was meant to be relaxed, a change of pace but while there, he stumbled upon a local startup event featuring short pitches, during which founders stood to introduce themselves. 

On impulse, he decided to pitch himself. He talked about his background, his interest in AI, and the projects he’d been building

He packed and moved from Seattle to San Francisco, committing fully to both roles. He lived in a hacker house – shared accommodation for founders and builders. 

“A hacker house is where a bunch of founders and startup people live in one apartment, hack, code, and build startups together,” he says. “I was building projects with a lot of people – it was really fun.”

Since both internships were unpaid, Utekar started looking for something more financially sustainable

And that included messaging Allen Wang, the CEO of Ditto AI, on LinkedIn. 

“I introduced myself and mentioned my experience working at startups and the projects I had built,” he says. “He connected me with the co-founder, Eric Liu, and I got onboarded. It was very seamless and amazing, and that’s how I started working at Ditto AI.”

At Ditto AI, Utekar joined as an AI engineer working on student matchmaking – think dating apps but for academic connections

His job was to automate matching and reduce manual work, simplifying workflows and keeping things running efficiently

Utekar considers it a major milestone to now work alongside Andrew Ng, the same person he once learned machine learning from

Early career moves that lead to big opportunities

As much as Utekar enjoyed his time at Ditto AI, he was looking for something more

He was interviewing for full-time roles while building a startup on the side when AI Fund came calling. The firm builds startups from scratch, exactly the kind of work he’d been drawn to throughout his career

It’s the same firm where Ng, the man behind the online course that started it all for Utekar years ago, is a managing partner at

“I interviewed at AI Fund and got a full-time offer,” he says. “Eventually, Ditto AI and one other company also offered me a full-time role, but my decision was easy. I wanted to join AI Fund.” 

In his current role as a technical builder at AI Fund, Utekar’s work looks very different from what he did before. Earlier in his career, he typically worked on a single product, spending months adding features and refining one system

At AI Fund, the focus is broader and faster. The team generates ideas internally, builds early versions, and quickly tests and validates them

Unlike most venture firms that invest in external startups, AI Fund builds them in-house. Utekar and his team take an idea from zero to one, validate it, and prepare it for founders who later take over. That early building phase is where most of his time goes, and it demands speed and constant experimentation

When asked for advice for students or early-career engineers entering applied AI, Utekar comes back to the same principle that carried him from a cyber café in India to San Francisco. 

“Start building projects using AI, because it’s very easy now,” he says. “You can build a product in a single day, like going from zero to one in a single day. Try to make something valuable, something people can actually use, and keep building.”

Source: studyinternational.com