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AI, ML, frontend, backend. Leverege is where it all fell into place.
My undergraduate degree was in electronics and telecommunication, but that was not quite where I ended up. After taking a few computer science courses, I got some hands-on experience as a software engineer at a bank in India and then decided to go back and do a master's in computer science to build a stronger foundation. I treated the master's as an opportunity to try everything — AI, ML, backend, frontend, all of it — and figure out which parts actually suited me.
When I started looking for my next job, I had a few clear priorities. The first was remote work: my husband was job hunting at the time and his options weren't going to be remote, so flexibility mattered for us to stay in the same place. Beyond that, I wanted to work in a field I was genuinely interested in, somewhere I could see the impact of what I was doing instead of feeling like a cog in a machine, with no visibility into the bigger picture. I was also looking for a company where I could build a long-term career, so longevity and opportunities for growth within the organization were important to me. And because I knew I'd be working remotely, I cared a lot about culture — I wanted somewhere that felt collaborative and inclusive even without a shared office.
I came across Leverege on LinkedIn, and as I did my research, I could tell the fit was excellent. From the blog posts from actual employees to the company team page covered with GIFs. This would be a fun place to work.
The interview process moved faster than anywhere else I was talking to, and everyone I spoke with made me feel comfortable. All of that together made the choice easy.
As soon as I started, I knew I’d landed in the right place. I found the AutoTrace team well-established, collaborative and, most importantly, open to hearing everyone’s opinions and thoughts on a problem. That's when I thought: okay, this is where I'm supposed to be.
The first few months were mostly about understanding the stack and how everything fit together, asking a lot of questions along the way. What surprised me was how much asking questions was actively encouraged. Often, the unspoken expectation is to figure things out on your own first and only ask for help once you've exhausted other options. Here it’s the opposite. I was encouraged to ask more so I could learn faster and build on what others had already figured out. It made the learning process not only faster, but a whole lot more pleasant.
I've recently moved to the team that develops WorkWatch, which supports manufacturing processes such as finding defects in wind turbine blades, using ML models to detect issues at different stages of production. It’s invigorating to be in the ramp-up stage again, but starting from a new base where I already understand the systems – and the company.
The most exciting thing right now is my first ML task. When camera settings on a customer's system changed, it meant our models had to change too. The goal is to update the augmentation setup, to solve this problem in advance in the future. Everything about it is new to me: what augmentations mean in practice, how to run and train the model locally, what we're actually trying to achieve. I had ML courses in my master's but that was a few years ago, and actually applying the principles is an exciting challenge.
The word I'd use for the culture here is collaborative. People help each other so that nobody feels isolated, even working fully remotely. For remote work to actually feel that way, you need the right structures in place, and I think Leverege does that well. Slack channels, standups, a friendly and responsive culture — those things matter more than they sound.
The thing I didn't expect was “donut chats.” Every week Slack randomly pairs you with someone from a different team for a 30-minute non-work conversation. It sounds small but I've genuinely connected with people I'd never otherwise interact with. When you're remote, your world can narrow to just the people on your immediate team, and donut chats prevent that from happening.
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