The biggest fear in tech right now is job security. With AI automating coding and other complex tasks, many aspiring Machine Learning Engineers are asking: “Will this job even exist by the time I break in?”
We sat down with Umang Chaudhary, a Machine Learning Engineer at TikTok who previously navigated his way from a traditional software engineering role into a specialized MLE position at Amazon. He’s seen the industry from the inside and now actively mentors others trying to break in, giving him a unique pulse on the market’s biggest anxieties and opportunities.
Umang cuts through the noise and delivers a tactical, reality-based roadmap for aspiring MLEs. He addresses the AI threat head-on, shares the exact framework he uses to help mentees land jobs, and explains why your mindset might be the single most important factor in your job search today.
In this episode, you’ll learn:
Why the fear of AI taking MLE jobs might be the wrong question to ask.
How Umang successfully navigated an internal transfer at Amazon to break into ML from a traditional SWE role.
A practical, four-step framework to structure your ML interview prep and avoid overwhelm.
The surprising LLM Umang uses for ML system design prep (hint: it’s not ChatGPT or Claude).
The critical difference between “real-world ML skills” and “interview-passing skills” - and which to prioritize.
Why patience and a “numbers game” mindset are your biggest assets in today’s tough job market.
If you’re feeling stuck or anxious about the future of machine learning careers, this conversation provides the clarity and actionable strategy you need to move forward with confidence.
Key Takeaways:
The best time to pursue an ML career is now. Instead of getting paralyzed by future speculation about AI’s impact, Umang argues that the opportunity is right in front of you. The path to becoming an MLE exists today, and focusing on what you can control and achieve right now is the most effective strategy.
Structure your interview prep to conquer overwhelm. Umang breaks down the daunting task of ML interview preparation into a simple four-part framework: ML Fundamentals, ML Design, ML System Design, and ML Coding. By tackling each component separately, you can create a focused, manageable study plan.
Treat your job search as a numbers game. In the current competitive market, patience is a strategy. Umang advises that it’s a funnel: aim for 100+ applications to get 10+ tech screens, leading to 4+ final round interviews to ultimately land that one offer you need.
Leverage AI as your personal interview coach. Many candidates are underutilizing LLMs in their prep. Umang reveals he uses tools like Grok to have comprehensive, multi-turn conversations about ML system design, effectively simulating a real interview and deepening his understanding on the fly.
Video Chapters:
0:00 The Future of Machine Learning Engineer Jobs
2:12 From Undergrad to ML Research in Singapore
4:50 The Internal Transfer: Switching from SWE to MLE at Amazon
9:30 Overcoming Early Interview Failures
12:00 Why Mentor? The Entrepreneurial Vision Behind Helping Others
15:50 How LLMs are Changing the Day-to-Day MLE Workflow
18:15 The Best LLM for ML System Design Prep (It’s Not ChatGPT)
21:49 From Web Dev to MLE: A Mentee’s Success Story
25:26 Interview Prep vs. Real-World Skills: What to Focus On
31:46 The #1 Advice for Today’s ML Job Market: Patience is Key
33:34 A Four-Step Plan to Break Into Machine Learning
Connect with Hai, Sravya, and Shane (let us know Substack sent you!):
#MachineLearning #MLE #DataScience #AI #LLM #CareerTransition #TechJobs #InterviewPrep #Amazon #TikTok #SystemDesign #JobSearch #TechCareer