Manoj Tumu, a 23-year-old machine learning engineer, recently made a significant career move from Amazon to Meta, securing a position with total compensation exceeding $400,000. His journey into the competitive AI field began in 2022, coinciding with ChatGPT’s release, which marked a pivotal moment when machine learning went mainstream.
Tumu’s accelerated academic path is remarkable: he completed his undergraduate degree in just one year by leveraging college credits earned during high school, then pursued a master’s degree in AI while working full-time as an engineer. After graduation, he landed a role at Amazon as a machine learning software engineer, where he spent nine months before being recruited by Meta.
At Meta’s Menlo Park headquarters, Tumu now works as a machine learning software engineer on an advertising research team, focusing on ensuring Meta utilizes the latest research and models to maintain its competitive edge. His role emphasizes research over implementation, requiring him to stay current with the rapidly expanding body of AI and machine learning literature.
Tumu highlights the evolution of machine learning from classical techniques—which relied heavily on human decision-making about data representations—to modern deep learning approaches that leverage artificial neural networks to automatically learn features from raw data. This shift has attracted significant investment from non-tech companies recognizing AI’s transformative power.
His career advice emphasizes several key strategies: prioritizing internships and work experience over personal projects on résumés, understanding that machine learning roles have varied titles across companies (research scientist, applied scientist, software engineer), and thoroughly preparing for behavioral interviews by studying company values. Tumu successfully navigated Big Tech’s standardized interview processes through cold applications without referrals, crediting his strong résumé built on relevant experience.
Notably, Tumu advises aspiring AI professionals to prioritize experience over compensation when starting out, sharing that he initially chose a lower-paying machine learning role over traditional software engineering positions—a decision that ultimately opened doors to his current high-paying position at Meta. His month-and-a-half interview process at Meta included four to six rounds covering coding, machine learning, and behavioral questions.
Key Quotes
Machine learning has gone mainstream. I started my master’s program in 2022, around the time ChatGPT was released. The advancement of AI and AI tools has made it a very competitive field, and many people are trying to get in.
Manoj Tumu explains how the release of ChatGPT marked a turning point that dramatically increased interest and competition in the AI field, transforming machine learning from a specialized discipline into a mainstream career path.
While I was at Amazon, I saw Meta doing a ton of cool machine learning things. When interesting roles came up, I just applied on their website or LinkedIn.
Tumu describes his motivation for leaving Amazon after nine months, highlighting Meta’s innovative AI work and demonstrating that cold applications can succeed even at top-tier tech companies without referrals.
Machine learning has shifted so much. 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.
Tumu articulates the fundamental technological shift in AI development, explaining how deep learning has replaced classical approaches and why this transformation has attracted widespread business investment in machine learning systems.
I chose a lower-paying machine learning role before I started working at Amazon, which I think really opened up more doors for me later.
Tumu shares strategic career advice for aspiring AI professionals, emphasizing that prioritizing relevant experience and learning opportunities over immediate compensation can lead to significantly better long-term outcomes in the competitive AI job market.
Our Take
Tumu’s trajectory exemplifies the AI talent war intensifying across Big Tech, where companies are willing to pay extraordinary compensation to secure skilled machine learning engineers. His $400,000 package at 23 reflects not just individual achievement but the strategic imperative driving Meta, Amazon, and competitors to dominate AI development. The emphasis on deep learning over classical techniques signals a maturation of AI methodology, where automated feature learning has proven superior to human-engineered approaches. Most telling is his advice to prioritize experience over projects—suggesting the field has evolved beyond theoretical knowledge to demand practical implementation skills. As AI becomes embedded across industries, career paths like Tumu’s will become increasingly common, with early specialization and continuous learning becoming prerequisites for success. The accessibility of his journey through cold applications, however, offers hope that meritocracy still functions in this hyper-competitive landscape, though the bar for entry continues rising rapidly.
Why This Matters
This story illuminates the explosive growth and competitiveness of the AI job market following ChatGPT’s 2022 release, demonstrating how quickly machine learning has transitioned from a niche specialization to a mainstream, highly lucrative career path. Tumu’s $400,000+ compensation package at age 23 underscores the premium Big Tech companies place on AI talent as they compete for dominance in the AI revolution.
The shift from classical machine learning to deep learning represents a fundamental transformation in how AI systems are developed, with implications for businesses across all sectors. Non-tech companies are now investing heavily in machine learning systems, expanding the job market beyond traditional tech hubs and creating opportunities across industries.
For aspiring AI professionals, this story provides a realistic roadmap emphasizing practical experience over academic projects, strategic career moves prioritizing learning opportunities over immediate compensation, and the importance of staying current with rapidly evolving AI research. As AI continues reshaping the economy, understanding these career pathways becomes increasingly critical for the next generation of tech workers navigating this transformative field.
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Source: https://www.businessinsider.com/quit-amazon-took-meta-ai-offer-how-to-land-job-2025-8