Insights from a Machine Learning Engineer at Meta
In an insightful essay for Business Insider, 23-year-old Manoj Tumu, a machine learning engineer at Meta, candidly shared his professional trajectory and offered invaluable advice for aspiring individuals aiming to penetrate the competitive realm of artificial intelligence.
Currently part of an advertising research team at Meta, Tumu disclosed that he secured a job offering with an exceptional total remuneration package exceeding $400,000 and highlighted essential strategies for a successful job hunt.
Understanding Your Role in Machine Learning and AI
Tumu articulated that the landscape of machine learning has undergone a significant transformation, evolving from traditional methodologies to a predominant emphasis on deep learning—an approach reliant on artificial neural networks that autonomously derive insights from data. The emergence of AI tools, such as ChatGPT, has intensified competition within this sector, resulting in a plethora of job titles that can often lead to confusion, including “machine learning engineer,” “applied scientist,” and “research scientist.”
His own position seamlessly synthesizes research with practical implementation, aiming to sustain Meta’s position at the industry’s cutting edge by leveraging the most recent advancements in research and models.
Emphasize Experience Over Projects on Your Résumé
According to Tumu, the paramount criterion for job applications is experience. He recommends that students endeavor to secure internships in any capacity during their college years. While he acknowledges the utility of projects, he believes they are often disproportionately emphasized on résumés. By the time he submitted applications to Amazon and Meta, he had strategically excised his projects, opting instead to accentuate his professional experience.
Tumu advises that after accumulating two to three years of experience, it is acceptable to remove project listings from your résumé. Notably, he did not depend on referrals to obtain positions at Amazon or Meta, opting to apply via their official websites or LinkedIn. His success in landing interviews, he attributes, was primarily due to a robust résumé grounded in substantial experience.
Avoid Common Pitfalls in Interview Preparation
One of the prevalent missteps Tumu has observed is the tendency to “wing it” during behavioral interviews. He underscores the importance of meticulous preparation, including a thorough understanding of the company’s core values and customizing answers accordingly. For instance, in his interview with Amazon, he prepared narratives aligned with its leadership principles.
He employed a similar strategy for Meta, which also delineates its values on its website. Tumu’s interview journey with Meta comprised an initial screening call followed by four to six rounds of coding, machine learning, and behavioral queries, spanning approximately six weeks.
Prioritize Passion Over Pay in Your Early Career
Lastly, Tumu emphasizes the need to overlook initial salary considerations when commencing one’s career. Reflecting on his own journey, he confesses he missed out on an internship during college but managed to secure a contract role shortly after graduation.
Faced with the choice between a machine learning position and a conventional software engineering role, he opted for the former, despite a lower salary, due to its greater appeal. This crucial decision, he asserts, eventually paved the way for broader opportunities as his career unfolded.
Source link: Timesofindia.indiatimes.com.
