Transitioning from finance to tech was no small feat for me. I always had an underlying interest in machine learning but felt unsure about how to make that leap. When I decided to take the plunge, I set a clear goal: land a junior ML engineer position within two months. It felt ambitious, but I needed that kind of urgency to keep myself motivated.

For the next two months, I dedicated myself to intense preparation. My days revolved around online courses, especially focused on Python and machine learning algorithms. I remember spending countless hours on platforms like Coursera and practicing coding problems on LeetCode. Balancing my time was tricky, and there were days I felt overwhelmed, but I kept pushing through, reminding myself of the end goal.

The interview process at JPMorgan was rigorous. There were three rounds: a technical interview, a take-home project, and a final behavioral interview. If I’m honest, the technical round threw me off my game. During one coding question, I completely blanked on a key concept related to decision trees, which I had just practiced the night before. I could feel my confidence wane for a moment, but I took a deep breath and managed to regroup before moving on to the next question.

When they called with the offer, my heart raced. It was surreal. All those late nights of studying were finally paying off. I felt a mix of pride and relief, knowing I had crossed a significant hurdle in my career. This journey was anything but smooth, but it taught me resilience and the importance of seeking help when needed. I’m excited to start this new chapter and would love to hear any advice from others who have made similar transitions.

Focus on core ML concepts first: understand the basics before diving deeper., Don’t shy away from coding practice; use platforms like LeetCode or Codewars daily., Build a small project to apply your knowledge; even a simple model can help reinforce your learning., Reach out to others in the field for mentorship; their insights can save you time and redirect your learning effectively., Prepare for real-life scenarios during interviews; practice behavioral questions as much as technical ones.