At just 23, Manoj Tumu has already lived through a career journey many engineers dream about. He was earning an eye-popping Rs 3.36 crore per year at Amazon, but earlier this summer he decided to walk away and join Meta instead.
Tumu, a machine learning engineer now based in Menlo Park, says the decision was less about money and more about the kind of work he wanted to do.
“I learned a lot at Amazon,” he told Business Insider. “But I saw Meta doing a ton of cool machine learning things. When an interesting role came up, I applied, and as soon as I got the offer, I knew I wanted to take it.”
In June, he left Amazon and started at Meta with a total compensation package of over $400,000. At Meta, he works on an advertising research team, where his job blends research and implementation, leaning more toward the research side. His focus is on keeping Meta’s machine learning systems up to date with the latest AI models and research.
A fast-track start
Tumu’s career has been nothing short of accelerated. He completed his undergraduate degree in just one year, thanks to college credits he earned in high school. By 2022, he was juggling a full-time engineering job while pursuing a master’s degree in artificial intelligence. That same year, ChatGPT arrived and suddenly the field of machine learning became hotter than ever.
After completing his master’s, Tumu joined Amazon as a machine learning software engineer. But within nine months, the lure of Meta’s AI projects pulled him away.
Lessons from his journey
Tumu says breaking into Big Tech is not as complicated as many think, but experience makes all the difference. While many candidates focus heavily on projects and programming languages on their résumés, he believes internships and real-world work matter far more.
“In college, try to get any internship, even the low-paying ones,” he advises. “Experience stands out the most. Once you’ve worked for two or three years, you don’t even need to list projects on your résumé. Focus on what you’ve done on the job.”
He also emphasizes preparing thoroughly for behavioral interviews, something many candidates underestimate. For both Amazon and Meta, he studied company values in detail and created a document full of stories to use in response to questions.
Looking ahead
Tumu is clear that his career choices have been guided by interest, not just paychecks. Early on, he chose a lower-paying machine learning role over a higher-paying software engineering role because the work excited him more.
That choice, he says, opened doors that eventually led him to Amazon and now to Meta.
For someone who has already reached a $400,000-plus package before turning 24, his advice is surprisingly grounded. “Don’t worry about pay when you’re starting out,” he says. “If you focus on learning and building experience, the opportunities will come.”
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