MS in the US (Your Journey + Advice)

Q1. Why did you decide to do an MS in the US?

I grew up reading and following about technological advancements in India, and after learning about stories of Apple, Google, and other tech companies I made a promise to myself that I’ll be working in Silicon Valley someday and MS was a stepping stone in that journey.

Q2. Do I need a perfect GRE or TOEFL score to get admitted?

No. My scores weren’t perfect in fact I didn’t got 0 admits and thankfully Illinois Tech was on india tour and offered me an on the spot admit for Masters in Computer Science program, but I think what mattered more was practical experience and clarity of goals. A strong profile is a combination of decent scores, impactful projects, internships, and solid recommendations.

Q3. How did you fund your MS?

Mostly through the student loan. I didn’t push myself to find on-campus jobs, instead I used that time to network in Chicago attending meetups Monday-Friday every evening learning about how companies are using AI and Data Science and getting to pick the brains of the people in the industry. Most people don’t realize universities offer teaching/research assistant roles that significantly reduce tuition and provide stipends.

Q4. Should I go for a high-ranked university or one with better funding?

Depends on your priorities. Brand helps in the long run, but assistantships and a supportive program matter too. I personally focused on the location of the University.

Q5. How different is studying in the US vs. India?

It’s more project-driven, discussion-heavy, and flexible. Professors expect you to be independent and proactive. You learn as much outside class—through networking and internships—as inside.

📊 Breaking into Data Science / AI

Q6. Do I need a PhD to work in Data Science/AI?

No. Many roles value applied skills over academic depth. If you’re strong in Python, ML frameworks, statistics, and can showcase projects, you’re employable. A PhD helps for research roles, but not for most industry ones.

Q7. What projects should I work on to get noticed?

Projects that solve real problems. For me, it wasn’t Kaggle competitions alone but applying ML to something tangible, like X. Recruiters love to see impact-driven work, not just tutorials. I used to participate in Hackathons because it pushes you to build something in a weekend with the time pressure and you also get a project under your belt which you can refer to in your resume.

Q8. How do I get my first break in Data Science?

Don’t wait for the “perfect DS role.” Start in adjacent roles—data analyst, ML engineer, or even SWE with data focus. Once inside, pivot. That’s how I navigated into AI/ML.

Q9. Is coding more important than math in Data Science?

Both matter, but most entry-level industry jobs value coding fluency and applied knowledge more. You don’t need to derive algorithms, but you should understand them enough to explain trade-offs.

Q10. How important is publishing papers?

Nice-to-have, not mandatory. In my case, practical experience and industry projects mattered far more.

🏢 Career Growth & Branding

Q11. How did you land your role at NVIDIA?

A mix of preparation and luck. I built credibility by sharing open-source work, networking, and positioning myself as someone who understood both tech and communication through my blogs, tutorials, and sharing my learnings as I took course or attended meetups/conferences. That visibility opened doors.

Q12. Do I need to network to get into Big Tech?

Absolutely. Cold applying rarely works. Networking doesn’t mean being fake, it means building genuine relationships and giving value before you ask.

Q13. What’s the single best thing I can do to stand out?

Share your work publicly. A GitHub repo, a blog, a LinkedIn post—even small things compound. Most people hide their progress; the ones who share get noticed.

Q14. How do you deal with impostor syndrome in Big Tech?

TBH I still face it and learning to overcome it by realizing that everyone, even senior engineers—feels it sometimes. What helped me was reframing: instead of “I don’t belong here,” I asked, “What can I learn from these people?”

Q15. Is personal branding really necessary?

Yes. People don’t just hire skillsets, they hire visibility and trust. Branding accelerates opportunities that skill alone would take years to reach.

🎤 Developer Advocacy / Public Speaking

Q16. What is Developer Advocacy?

It’s the intersection of engineering, communication, and community-building. You write code, create content, share with the community, and represent developers inside and outside your company.

Q17. Do you need to be an extrovert to succeed in DevRel?

Not at all. I used to be shy and camera-conscious. What matters is empathy for developers and the willingness to communicate in any format, blogs, videos, or talks, and with time and enough reps anyone can get good at communicating succinctly.

Q18. How do you prepare for public speaking?

Toastmasters, I have been part of it for last 4 years and helped me tremendously. Also, practicing out loud, not just in your head helps. I also reframe nerves as energy—if I’m nervous, it means I care. Over time, the stage stopped being scary and became exciting.

Q19. How do you balance technical depth vs. simplicity when explaining?

By having empathy about where they come from and by always asking: “What’s the one thing I want my audience to take away?” Then tailoring depth depending on whether I’m talking to beginners, practitioners, or experts.

Q20. How do you become a Dev Advocate?

Start before you have the title. Write tutorials, speak at meetups, contribute to open source. Companies notice people already doing advocacy—then they formalize it into a role.

🔄 Staying Current & Tools

I usually use X and Reddit /LocalLlama subreddit to follow all the advancements. I have also created a curated X (twitter) list with top people/toosl in LLMs/agents space here so it’s easy to follow for anyone.

Q22. How’s your experience working at NVIDIA?

This is my first full-time job, so I can’t compare but it’s absolutely amazing to work here, I get to work with some of the smartest people on the planet and learn at the speed of light as NVIDIA always stays at the forefront in the AI space. Also, Jensen is a once in a generation leader, and quite revolutionary like Steve Jobs in terms of bringing ground breaking changes to tech ecosystem.

Q23. What AI tools do I use daily?

Here are the AI tools I use daily:

  • Coding: Cursor and Gemini CLI
  • Browsing: Perplexity Comet
  • Writing: ChatGPT
  • General AI tasks: Gemini
  • Driving: Tesla FSD
  • Video editing: Adobe Premiere Pro
  • Recording talks: Voice Memos (I record talks at meetups/conferences, transcribe them, and use LLMs to summarize)
  • Learning from videos/blogs: NotebookLM (great for understanding YouTube lectures, technical videos, and long-form blogs)
  • Research: Gemini Deep Research (for understanding trends)
  • Voice brainstorming: Sesame Voice Preview app and ChatGPT Advanced Voice (for brainstorming via voice chats)

I’m always experimenting with new tools to see what works best. For example, I’m currently trying out Alibaba’s Qoder and the LMStudio desktop app to run LLMs locally.

I also frequently use Gemini Live with Camera to point at things and ask questions or get help fixing something. For audiobooks, I use ElevenLabs to generate audio versions of digital books.

Q24. What do you do for productivity and how do you avoid procrastination?

I still struggle with procrastination sometimes, but shifting my mindset and asking myself why I’m procrastinating helps. Usually, starting with a small task makes it much easier to build momentum and make real progress. For the past six years, I’ve used Focusmate.com, which pairs me with an accountability partner on demand—this has been a huge help in getting started and staying productive.

🌍 Current Market & Advice

Q25. Do you recommend coming to US right now?

I don’t, it’s really bad in terms of job market, and with AI tools becoming more mainstream, experienced professionals are much more in advantage with these AI tools than early career grads. It might be a huge risk if you still plan to come to US.

Q26. What would you have done if you were in this job market?

I would have done same things that I did in Masters, which was attending meetups, network with professionals by being curious, participate in as many hackathons as possible, and write/share whatever you learn in public through GitHub/blogs/videos, etc. This might not gurantee the job but will signifciantly raises the chances to land an interview.