Published on: August 29, 2025 10:29 AM IST
23-year-old Indian-American engineer Manoj Tumu, who left Amazon for a $ 400,000 AI role in Meta, shared advice for students and job seekers.
A 23-year-old Indian-American machine learning engineer in Meta shared insight into his career trip and has given practical advice for students and job seekers, which aim to break into artificial intelligence. Manoj Tumu, who works in Meta’s advertising research team, included Amazon in a role to join the social media veteran, which is more than $ 400,000, the total compensation package that translates 3.36 crores in India.
In an essay for Business Insider, Tumu explained how he navigated the process of competing work and the lessons that shaped his career path.
Tumu stated that the field of machine learning has moved rapidly in recent years, moving from classical techniques to deep learning operated by the nerve network. The rise of devices like Chatgpt has further intensified the competition by making various job titles such as machine learning engineers, applied scientists, or research scientists. His own position in Meta combines research and implementation, aims to ensure that the company remains on the state -of -the -art edge of AI.
Why experience more than projects
When it comes to the resume, Tumu emphasized the importance of professional experience on individual projects. He encouraged students to secure the internship while staying in college, explaining that the projects are useful quickly, they should eventually take a seat. By the time he applied for roles in Amazon and Meta, he had completely removed the projects to highlight the work experience. He also noted that he did not rely on the referral instead of applying directly through the company’s websites and linked, with a strong resume heavy lifting.
Tumu warned against being unmoved in behavior interview, calling it one of the biggest mistakes. He advised to answer the values of the company, as he had done while preparing Amazon’s leadership principles and the corporate values of the meta. His meta interview process included a screening call, followed by four to six round coding, machine learning and behavioral questions in six weeks.
While reflecting his early career, Tumu admitted that he missed an internship during college, but managed to secure the role of a contract after graduation. When selecting between machine learning and traditional software engineering, he opted for a low-paying role in machine learning as it aligned with their interests. This decision, he said, eventually opened the door for better opportunities, including his current position in Meta.
