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Why Manoj Left a 3.36 Crore Amazon Job at 23

TL;DR

• Manoj Tumu, a 23-year-old Indian-American engineer, left his ₹3.36 crore (over $400,000) job at Amazon for an AI research role at Meta.
• He believes relevant work experience outweighs personal projects for top tech jobs.
• His decision was fueled by the rapid evolution of machine learning and his passion for AI innovation.

Introduction: Rethinking Conventional Tech Career Wisdom

In a competitive world where high salaries at Big Tech companies are considered the pinnacle of achievement, Manoj Tumu’s career move stands out. At just 23, he made headlines after quitting his ₹3.36 crore per annum job at Amazon for an equally demanding position at Meta (formerly Facebook). His journey underscores why real career growth is about more than just compensation, and offers practical advice for anyone looking to break into artificial intelligence and machine learning today.

The Journey: From Amazon Gold to Meta AI Innovation

The Temptation of a High-Paying Tech Job

For most young professionals, a job at Amazon with a ₹3.36 crore ($400,000) package would be a career dream come true. Yet, for Manoj, it was a starting point—a launchpad, not a destination. He was already thriving as a machine learning engineer within Amazon’s sophisticated digital ecosystem, but noticed the landscape was changing faster than ever, especially in the field of AI.

Why Did Manoj Make the Move?

Several factors motivated Manoj to resign:

• Desire to Be at the Cutting Edge: Machine learning rapidly shifted from classical techniques to deep neural networks. Companies like Meta were investing heavily in generative AI and targeting new frontiers.
• Passion for Impact: Rather than just implementing known solutions, Manoj wanted his work to directly influence research and application in next-gen AI, which Meta promised.
• Long-Term Career Value: Manoj recognized that high salary alone couldn’t guarantee career satisfaction or growth. Skill progression, innovation, and domain expertise meant more in the evolving AI economy.

Behind the Scenes: How Manoj Landed Top AI Jobs Without Referrals

The Importance of Strategic Resumes

New grads and job switchers often focus their resumes on personal projects, but Manoj saw differently. Relevant, real-world experience was what hiring managers at top tech companies prioritized. Here’s how Manoj crafted his applications:

• Internships and Contract Roles: Despite missing out on an internship during college, he compensated by securing a contract role after graduation. This hands-on experience later opened doors at Amazon and Meta.
• Resume Refinement: As his professional experience grew, Manoj removed project work from his resume—highlighting practical skills, business impact, and teamwork instead.
• No Reliance on Referrals: Contrary to popular wisdom, Manoj landed interviews at Amazon and Meta by directly applying online, through career sites and LinkedIn—proving that a strong, well-targeted resume speaks for itself.

The Harsh Truth About Behavioral Interviews

According to Manoj, one of the most common mistakes candidates make is taking behavioral interviews lightly. To succeed:

• Research Company Values: Manoj tailored his responses to align with Amazon’s Leadership Principles and Meta’s company values, which demonstrated cultural fit and self-awareness.
• Practice Makes Perfect: He rehearsed answers to common behavioral questions and related anecdotes from his own work history, ensuring authenticity.
• Rigorous Technical Rounds: The Meta interview process spanned 4-6 rounds, assessing coding fluency, machine learning acumen, and situational judgment over six weeks.

Lessons from Changing Tech Tides: AI, Deep Learning, and the Rise of Specialization

AI: From Buzzword to Real-World Impact

Manoj started his journey during a pivotal time for machine learning:

• Neural Networks and Deep Learning: The shift from classical ML to deep learning changed the skills required, upped the competition, and created both new job categories and new challenges.
• The ChatGPT Effect: Generative AI tools made AI mainstream, increasing demand for specialists who could not only code, but also innovate at scale.

Choosing the Right Path: Experience vs. Salary

After college, Manoj faced a decision: take a higher-pay software engineering job or opt for a specialized role in machine learning. He chose the latter—even though it paid less at the outset. His reasoning:

• Passion Over Paycheck: Working in a field he loved was more sustainable for the long term.
• Specialization as a Superpower: Expertise in machine learning accelerated his career far more than a generic engineering background.
• Opening Doors: By prioritizing learning and experience, Manoj accessed advanced opportunities—ultimately landing higher-paying, more fulfilling roles like his current Meta position.

Key Takeaways: How to Break into AI and Build a Future-Proof Career

1. Get Real Experience Early
   Don’t overlook internships or contract work—these experiences stand out to recruiters and help you develop both technical and soft skills.
2. Focus Your Resume on Impact, Not Just Projects
   Highlight the business or research impact you’ve had—not just side projects.
3. Prepare Extensively for Interviews
   Research company values and practice behavioral as well as technical questions. Genuine, contextual answers beat rehearsed buzzwords.
4. Apply Broadly and Directly
   Don’t wait for referrals. A strong, well-crafted online application can land you interviews with the world’s most competitive companies.
5. Choose Passion Over Immediate Pay
   If you can afford it, pursue the field that excites you most, even if it pays less initially. Over time, your passion and expertise lead to exceptional roles—and pay.

Manoj’s Advice for Students and Early-Career Professionals

• “Projects are essential at first, but experience soon matters more as you build your career. Make each internship count.”
• “Don’t neglect behavioral interviews. Align your stories with what the company truly values—and be authentic.”
• “It’s okay to start from a lower-paid, meaningful job; specialization is more important for long-term growth than salary alone.”

The Future of AI Careers: Are You Ready?

AI and deep learning are advancing at breakneck speed. Companies like Meta, Google, and Amazon are hungry for machine learning talent that goes beyond the basics. As Manoj’s unique journey shows, standing out in this world takes focus, patience, and a willingness to choose growth over comfort.

If you’re a job seeker, student, or early-career professional interested in artificial intelligence, now is the time to double down on learning, embrace every opportunity for real-world experience, and dare to think beyond job titles to the impact you want to make.

Frequently Asked Questions

Q1: Why did Manoj Tumu leave a ₹3.36 crore job at Amazon for Meta?

A: Manoj sought greater opportunities for innovation and impact in artificial intelligence. He wanted to be at the forefront of AI research and chose Meta for its cutting-edge projects, even though he was already receiving a high salary at Amazon.

Q2: What matters more for landing jobs in AI—personal projects or work experience?

A: According to Manoj, while projects help early on, real-world experience (internships, jobs) is much more valuable to recruiters at leading tech firms. Over time, prioritize actual professional contributions.

Q3: How can I prepare for behavioral interviews at top tech companies?

A: Study the core values of the companies you’re applying to. Tailor your examples to demonstrate those values. Practice not only technical, but also situational and behavioral questions with real, authentic stories from your experience.

Conclusion: Success Is About Growth, Not Just Salary

Manoj’s story is a testament to following your passion for innovation and strategically investing in your own growth—even if it means leaving money on the table in the short term. For anyone aspiring to build a robust career in AI, his path is rich in lessons: prioritize learning, impact, and authenticity over immediate titles and compensation. The future rewards those who build their skills, take risks, and stay relentlessly curious.

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