HCLTech Interview Questions
& Process

My interview with HCL went really well, and they told me in five minutes that I was moving to the next stage, with HR supposed to contact me. But then, a whole week went by with no word. Suddenly, an HR person hit me up on LinkedIn saying the job went to another vendor. Super disappointing. If they weren't gonna move forward, they should have just said I didn't pass or they weren't continuing. Instead, I was left hanging for a week with false hope, and then got that news later, which felt pretty unprofessional.

It's pretty straightforward. First, you apply. If they like your resume and you pass the ADS, you'll get a chance to send in a video answering five pre-recorded questions they email you. If they like that, a manager will reach out for an interview. There's just one interview round, mostly asking about your knowledge of HCL Tech, its operations, verticals, and general company processes, as well as about you. If you get through that, you'll be offered a remote internship.

The interview process started with an initial screening round which was pretty easy and basic, mostly just to filter candidates. It wasn't super technical, but they wanted to know about my background and experience, the basics of my core skills that I listed on my resume, and some simple scenario-based or conceptual questions depending on the role. For example, they might ask about my current project, my role and daily tasks, or basic concepts like architecture, workflow, and lifecycle. They also checked my communication skills and clarity, and sometimes discussed availability, location, and salary expectations.

It was like a hackathon to see if I had the technical chops and could solve real problems. They gave me a real-world problem and a time limit. I had to figure out the problem, prep the data, engineer features, pick a model, train it, and see how well it did. It was all about practical ML stuff, not just theory. They checked my code quality, logic, algorithm choices, and my overall strategy. I had to explain my choices, what I assumed, and what the results meant. They judged me on if I got the right answer, if it was clear, efficient, and if I could actually make something that worked on time. Basically, it was a hands-on test of problem-solving, ML basics, and getting things done like in a real dev job.