How To Switch From Software Dev to Machine Learning Engineer (Amazon SDE -> Tiktok MLE POV) - w/ Umang

In this episode of Ready Set Do, my guest is Umang Chaudhary, a Machine Learning Engineer at TikTok and former Applied Scientist at Amazon. Umang’s story is one of momentum — a reminder that you don’t need decades of experience to reach the top tiers of tech. What matters more is the mindset: continuously learning, adapting fast, and being ready to leap when opportunity strikes.

We dive deep into how Umang built his way into machine learning roles in Big Tech without prior ML experience, and the exact principles that helped him accelerate his career both internally at Amazon and externally to TikTok. His path shows that success in tech isn’t about luck — it’s about strategic preparation, deliberate skill-building, and understanding where the industry is heading next.

Umang breaks down his early struggles, from navigating graduate school in the U.S. to handling the uncertainty of job hunting as an international student. He explains how to find leverage in every stage of your journey — whether that’s converting an internship into a full-time offer, pitching yourself for roles outside your comfort zone, or developing credibility in a field as competitive as machine learning.

We also talk about the hidden truth of career acceleration: the importance of consistency over intensity. Umang shares how he prepared for months before landing interviews, why most people give up too early, and what separates those who get rejected once from those who eventually break into elite teams. His advice on managing rejections, reframing failures, and staying mentally sharp during transitions is refreshingly real and actionable.

Another major insight from this episode is Umang’s perspective on risk and adaptability inside Big Tech. At Amazon, he learned how scientific rigor meets business impact — and how every algorithm, no matter how elegant, must tie back to measurable outcomes. Moving to TikTok introduced a whole new dimension of risk management, scale, and data culture. We discuss how these environments differ, what machine learning looks like behind the scenes in companies like TikTok, and how engineers can future-proof their skill sets as AI continues to evolve.

For anyone eyeing a transition from software development to machine learning, this conversation is a masterclass in how to position yourself for that leap. Umang breaks down what kind of projects actually stand out on a resume, how to build a real portfolio even without official ML job titles, and how to think like an applied scientist before you even become one.

Whether you’re a student preparing for your first ML interview, a software engineer exploring a move into AI, or a professional stuck wondering what your “next big jump” could be — this episode will give you a framework to act, not just plan.

It’s a story about breaking inertia, not waiting for permission, and redefining what “ready” really means.

🎧 Listen now to learn how Umang built his way from Amazon to TikTok, how he approaches learning as a lifelong system, and how you can apply the same principles to build a faster, more intentional career in tech.

Follow Umang on Instagram: @umangabroad
Explore all links and episodes: readysetdopodcast.com

Timestamps:

00:00 Intro + Background
04:36 Controversial Opinions on Moving to the US
07:03 Opportunities in the US for Future Students
10:55 Master's Journey and Lessons Learned
16:15 Internship Experience at Amazon
25:31 Transitioning Roles at Amazon and Career Growth
30:36 Navigating the TikTok Interview Process
32:27 Prioritizing Preparation for Interviews
35:03 Learning from Rejection: The Journey to Success
37:12 The Importance of Consistent Preparation
39:41 Motivation Behind Career Transitions
41:23 Understanding TikTok's Role in Risk Management
43:20 Future Aspirations and Mentorship in ML