Career Journey of Manoj Tumu: Insights from a Machine Learning Engineer
From Amazon to Meta: A Promising Transition
At just 23, Manoj Tumu, an Indian-American machine learning engineer, has made a significant career transition from Amazon to Meta, securing a total compensation package exceeding $400,000 (₹3.36 crore). In an enlightening article for Business Insider, he shared valuable insights into his career journey and offered advice for aspiring engineers.
Tumu expressed his enthusiasm about joining Meta, stating, “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 elaborated on his decision by saying, “Though I had learned a lot at Amazon, I just thought there was more interesting work going on at Meta.” This statement highlights the importance of passion and interest in one’s career choices.
The Importance of Real-World Experience
Tumu emphasized the value of real-world experience over personal projects during job applications. He encouraged students to prioritize internships, even those that may offer minimal pay.
“When I see the résumés that people post online, asking for advice, I see projects or programming languages taking up space,” he noted. “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.”
Networking and Application Strategies
Rather than relying on referrals, Tumu applied directly through company websites and LinkedIn, ensuring that his résumé stood out. This proactive approach underscores the importance of self-advocacy in the job market.
Preparing for Interviews
Tumu highlighted the critical role of preparation for behavioral interviews, describing lack of preparation as a major pitfall candidates encounter.
He recounted his experiences during the hiring processes at both Amazon and Meta, which included multiple rounds of interviews covering coding, machine learning, and behavioral questions.
“I studied the company’s values to prepare for the behavioral interview and had a huge document where I would write down stories to answer possible questions along with follow-ups,” he shared. This meticulous preparation helped him present himself as a well-rounded candidate.
He advised job seekers to familiarize themselves with a company’s principles and tailor their answers accordingly, enhancing their chances of success.
Reflecting on Early Career Choices
Tumu candidly admitted that he missed out on internships during college, yet he managed to secure a contract role after graduation. Faced with the decision between traditional software engineering and machine learning, he opted for the latter despite its lower initial pay, driven by his passion for the field.
This choice, he notes, eventually led to better opportunities, including his current role on Meta’s advertising research team, showcasing the importance of aligning career choices with personal interests.
Transformations in AI and Machine Learning
According to Tumu, artificial intelligence has undergone dramatic changes in recent years, evolving from classical techniques to deep learning approaches.
“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 acknowledged the variability of job titles in the sector, which include roles such as research scientist, applied scientist, software engineer, or machine learning engineer. This diversity reflects the evolving landscape of AI and machine learning.
Conclusion
Manoj Tumu’s journey illustrates the value of passion, preparation, and real-world experience in building a successful career in machine learning. His insights serve as a beacon for aspiring engineers aiming to navigate the competitive landscape of technology.
Questions and Answers
1. What motivated Manoj Tumu to transition from Amazon to Meta?
Tumu was motivated by the opportunity to work on more interesting projects at Meta, which he believed aligned better with his career goals.
2. What advice does Tumu give students regarding internships?
He advises students to prioritize real-world internships, even if they offer low pay, as these experiences are more valuable than personal projects on résumés.
3. How did Tumu prepare for his interviews at Amazon and Meta?
Tumu prepared by studying the companies’ values and creating a document with stories to respond to potential behavioral questions.
4. What career choice did Tumu make after college and why?
He chose machine learning over traditional software engineering due to his strong interest in the field, despite the initial lower pay.
5. How has the field of artificial intelligence changed according to Tumu?
Tumu noted that the focus has shifted from classical techniques to deep learning, which allows for automatic feature learning using artificial neural networks.
