From Mechanical Engineer to Full-Stack Developer – My Unconventional Journey

"Wait, You're a Mechanical Engineer?"

"So, you studied mechanical engineering? You must love designing engines!"

Me, staring at an endless stream of console logs as my dev server crashes from an infinite rerender caused by a bad useEffect: "Yeah... about that... now I just engineer infinite loops."

If I had a rupee for every time someone looked confused when I explained my career trajectory, I could probably fund my startup for another year. But that's the beauty of unconventional paths—they make for much better stories.

The Beginning – Why Mechanical Engineering?

My journey began in Kerala, India, where I spent my formative years at Loyola School. Computer science entered the curriculum in 6th grade, but it wasn't until 8th grade that we tackled "serious" programming. Truth be told, I was initially terrible at it (not perfect, but I’ve come a long way). With a father who was an athlete and coach, computer time was strictly limited in our household. Playing games was practically forbidden (though I'd occasionally sneak in some gameplay at my neighbourhood friends' houses). So when programming lessons began, I floundered.

Everything changed when my parents hired a tutor—a working professional with infinite patience who opened up a whole new world of coding. Under his guidance, my grades improved, and I developed a decent grasp of Java. By the end of high school, I had options to consider. Despite being reasonably good with Java by then, I had zero interest in pursuing computer science as my degree. The idea of "sitting at a computer and coding away" seemed utterly monotonous. Instead, I was drawn to automobiles—not just their mechanical aspects, but their design.

After weighing my options and getting advice from a family friend in education consulting, I decided on a strategic approach: pursue mechanical engineering for my undergraduate degree, then specialize in automobile design for my master's. I was so committed to this path that when filling out my college preferences, mechanical engineering was the only option I selected.

The "Wait... Do I Actually Love This?" Moment

Reality, as it often does, had other plans. My mechanical engineering experience was nothing like I'd imagined. The syllabus was so outdated it might as well have been from the previous century—not that fundamentals weren't important, but we never learned anything new. I found myself dragging through four years of education.

Then there was COVID-19, eliminating the only enjoyable part of the program—the practical sessions. Stuck at home without access to parts or equipment, I couldn't pursue any mechanical projects. For the first time, I seriously questioned my chosen path. During this period, our college partnered with Coursera to offer online courses. With Python gaining popularity, I thought, "Why not try it?" People kept saying it was easier than other languages. While I completed the course, it didn't immediately reignite my passion—my mind was elsewhere, panicking about an uncertain future.

In my final year, a glimmer of hope appeared when I joined Team Pravega, gearing up for the Shell Eco-Marathon. Working on body and chassis design rekindled some of my old enthusiasm. But the true eye-opener was developing a driver awareness system—my first real exposure to computer vision applications. It was fascinating, to say the least, and for the first time in a long while, I felt a genuine desire to learn something new. Yet despite this positive development, I remained unsure about my future. When recruitment season began at college, the options were disheartening: tech companies offering severely underpaid positions with extended hours.

Enter: The World of Code

Post-graduation, YouTube became my career counsellor. I stumbled across a video about a full-stack engineer who transitioned to AI/ML. His journey resonated with me, suggesting that full-stack experience could serve as a stepping stone. Around the same time, the algorithm gods delivered an advertisement for a full-stack course by Crio.do. Their marketing was so compelling that I thought, "If I build these skills, I could gain confidence and eventually transition to AI/ML." With this rationalization, I enrolled in the year-long course.

Something unexpected happened during that year—I fell in love with coding, especially front-end development. Creating interactive interfaces and experimenting with animations was genuinely fun, a stark contrast to my earlier perception of programming as monotonous.

The reality check came when I started job hunting. Most companies were doing mundane work, creative positions required work permits I didn't have, and entry-level roles were practically exploitative. The most frustrating part? Companies let me sit through interviews, clear them, move on to the coding rounds, and even reach the final stage—only to reject me in favour of someone with experience. When I followed up, the response was always the same: they had found a candidate with experience. But if that’s what they wanted, why drag me through all these rounds, raise my hopes, and waste my time? The lack of transparency was as disheartening as the rejections themselves.

During this time, I began teaching front-end development to my friend Aswin (who I'd met through online games, of all places). He had quit his job and wanted to try something new. Little did we know this casual teaching arrangement would lead to something bigger.

AI & Data Science: The Next Evolution

A conversation with an old friend—an alignment researcher—reignited my interest in AI/ML. When he asked about my progress, I realized I'd been neglecting this path. On his recommendation, I applied to the Fundamentals of AI Safety program by Bluedot Impact and, to my surprise, got accepted. Despite being the least experienced participant, I dove headfirst into AI/ML theory just to keep up with the sessions. The experience was eye-opening, connecting me with brilliant minds from around the world. For my mandatory project, I researched Reinforcement Learning from Human Feedback (RLHF) and titled it "Journey Through Reinforcement Learning: A Beginner's Exploration." The project was fulfilling, but I felt something was missing—structure. After so much self-learning, I craved formal education in the field. I began looking into master's programs in Data Science, believing a solid foundation in data would help me branch out into specialized AI/ML roles later.

Meanwhile, I was freelancing as a developer when a mutual friend, Sarvesh, approached Aswin and me with an intriguing proposition: "I have a client willing to pay more than any client you've had so far, but we need to establish a company to seal the deal." And that's how Ernyg was born.

Lessons Learned Along the Way

Everything is Learnable

Coming from mechanical engineering, I initially felt disadvantaged in the tech world. But I quickly realized that technology isn't about degrees—it's about problem-solving and persistence. If you can break down complex problems and have the tenacity to push through challenges, you can learn anything.

Breaking Out of Comfort Zones

Every significant growth in my journey—from traditional engineering to full-stack development to AI safety—happened because I was willing to try something unfamiliar. The moment you start feeling too comfortable is exactly when you should consider stretching your boundaries.

Imposter Syndrome Never Really Leaves

Throughout my journey, I've felt like an impostor in every field—doubting myself during my mechanical engineering studies, feeling worthless after job rejections despite having the skills to reach the final rounds, and even feeling out of place in the AI Safety course. But I've learned that even experts experience this. The key is to view it as a learning opportunity rather than a debilitating condition.

What's Next?

Currently, I'm at a crossroads that feels more like a convergence—running Ernyg while preparing for the next chapter of formal education. With admissions secured at Arizona State University and the University of Michigan, I'm looking forward to deepening my knowledge in data science.

My goal isn't just to bridge AI, software, and data science, but to approach these fields with the unique perspective of someone who's navigated the mechanical world and understands some of its challenges. There's something powerful about bringing an outsider's perspective to established fields.

If you've ever thought about switching careers or learning something completely new, I have one piece of advice: go for it. The path won't be linear, and there will be moments of doubt, but those diversions often lead to the most interesting destinations and experiences.

And if you're already on that journey, I'd love to hear your story! Connect with me through the social links on my author page—after all, the best part about unconventional paths is comparing notes with fellow travellers.