At only 23 years of age, Manoj Tumu, an Indian-American software engineer, had secured a position at Meta, earning a total annual compensation package of approximately $400,000 (Rs 3.52 crore). He previously worked at Amazon before joining the social media company’s advertising research team earlier this year.
In an article he wrote for Business Insider, Tumu explained that he had left Amazon in June to take up the new role. “In June, I left Amazon to join Meta as a machine learning software engineer for a total compensation of over $400,000. I was really excited about it and knew I wanted to take the job as soon as I got the offer,” he stated.
Although he credited Amazon with giving him valuable professional experience, Tumu said he was drawn to the scope of projects at Meta. “Though I had learned a lot at Amazon, I just thought there was more interesting work going on at Meta,” he remarked.
Reflecting on the wider industry, he wrote that artificial intelligence and machine learning had advanced considerably in recent years. “It used to be a lot more acceptable to just use classical techniques, which rely on humans to make decisions about data representations. Now the focus is on deep learning, which taps into artificial neural networks to automatically learn features from raw data,” he explained.
He also noted that job titles in the field could vary significantly, sometimes being described as research scientist, applied scientist, software engineer, or machine learning engineer, depending on the company.
For students, Tumu emphasised the importance of gaining experience through internships, even if the pay is modest. “Even low-paying internships can be beneficial for a machine learning career, and [you should] not worry about the pay,” he advised.
Tumu, who began his master’s degree in 2022, highlighted experience as the main factor in securing roles in major technology firms. He said he relied on a strong resume and persistence rather than personal contacts. “I left cold emails. My decent resume helped me secure my jobs at Meta and Amazon, as I did not have a reference for either of the companies,” he wrote.
On reviewing other candidates’ resumes, he suggested that once an individual had built two to three years of work experience, they should shift the focus from university projects to professional contributions. “My general advice would be that once you have two or three years of experience, it’s OK to remove the projects and focus more on highlighting your experience,” he said.
Tumu also warned job seekers about common mistakes in behavioural interviews. Describing his own experience, he recalled, “I went through six rounds of interviews at Amazon where they asked coding, machine learning, and behavioural questions.”
He explained that he had studied Amazon’s leadership principles in detail to prepare, creating extensive notes. “I studied the company’s values to prepare for the behavioural interview and had a huge document where I would write down stories to answer possible questions along with follow-ups,” he noted.
His recommendation to candidates was to prepare in a similar way: read the company’s stated values carefully and adapt answers to suit the examples being assessed.
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