A 23-year-old Indian-American machine learning engineer at Meta has shared insights into his career journey and offered practical advice for students and job seekers aiming to break into artificial intelligence. Manoj Tumu, who works in Meta’s advertising research team, left Amazon to join the social media giant in a role that offers a total compensation package exceeding $400,000, which translates to ₹3.36 crore in India.
In an essay for Business Insider, Tumu explained how he navigated the competitive hiring process and the lessons that shaped his career path.
Tumu said the field of machine learning has shifted rapidly in recent years, moving from classical techniques to deep learning powered by neural networks. The rise of tools like ChatGPT has further intensified competition while creating varied job titles such as machine learning engineer, applied scientist, or research scientist. His own position at Meta combines research and implementation, aimed at ensuring the company remains at the cutting edge of AI.
Why experience matters more than projects
When it comes to résumés, Tumu stressed the importance of professional experience over personal projects. He encouraged students to secure internships while in college, explaining that while projects are useful early on, they should eventually take a back seat. By the time he applied for roles at Amazon and Meta, he had removed projects entirely to highlight work experience. He also noted that he did not rely on referrals, instead applying directly through company websites and LinkedIn, with a strong résumé doing the heavy lifting.
Tumu cautioned against going unprepared into behavioural interviews, calling it one of the biggest mistakes candidates make. He advised tailoring answers to company values, as he did when preparing for Amazon’s leadership principles and Meta’s corporate values. His Meta interview process included a screening call followed by four to six rounds of coding, machine learning, and behavioural questions over six weeks.
Reflecting on his early career, Tumu admitted he missed out on an internship during college but managed to secure a contract role after graduating. When choosing between machine learning and traditional software engineering, he opted for the lower-paying role in machine learning because it aligned with his interests. That decision, he said, eventually opened the door to better opportunities, including his current position at Meta.