I got my bachelor's and master's degree in computer science and then migrated to the United States for my Ph.D. program at the University of Denver. In the third year of my Ph.D. I did an internship at Google. Then last year I did another internship at Twitter and then I liked the team that I was working with so I joined Twitter full-time about two years ago. During that time I worked with the team which was more focused on natural language processing for understanding the tweets, it's contents and provide these as a signal to other teams at Twitter for a better recommendation, user understanding, push notifications as targeted and so on.

I'm the tech lead of the team at Twitter. I can explain what are the stats so we have a manager who works on the human management team planning and staffing of the projects and then we have individual contributors who we call IC's. For example in our team we have a programmer, machine learning engineers who work on the field projects and then the role of the tech lead is somewhere between the manager and IC's. So my work is specifically is focused on technical planning, helping the manager to come with the road maps, and in terms of IC's when they join our team I help them to get on board and overall for interaction with IC's. I work with them on planning code reviews and ensure that the code quality at our team is up to the standards that we care about. Twitter highly valued the distributed offices and so currently we have different offices in San Francisco, Seattle, Boulder, New York, Boston and London. My team is also very distributed so we have folks in San Francisco, I worked in Boulder on other teams also in New York and we are expanding on the Boston office. I work on a lot of things for example with different folks in different offices. We have to coordinate with a lot of meetings during the day so that we make sure that we are on the same page. At Twitter we have work from home policy and it's paid. We have this flexible policy that we can work from anywhere and basically that makes our job easier and it makes us more focused. In terms of my daily work and responsibilities as I mentioned a lot of things come back to coordination between different teams. I kind of play the role of a representation of my team to other teams at Twitter. So then the customer request comes to our team. For example, Team wants to incorporate machine learning signals into their production than we have this coordination meeting and make sure that we can tell there on time and we can provide those machine learning understanding based to the customers at Twitter. So it's a mixture of having a lot of meetings as well as on my own side. I have technical responsibility for the project I personally lead or work on the team every day so it's a mixture of programming and coordination with other team members.

At Twitter we highly used scholar as a backbone of our services and then it's functional programming that makes a lot of trading and a lot of distributed programming a lot easier. On the machine learning side we use a lot of python and TensorFlow for learning new models and deploy them into the production. I don't have a preference and it's sort of advice to all the students that when you learn programming languages it is not like learning German and English. it's totally different language, in the programming language, if you learn the bare bone of programming algorithms and how to implement a problem or ought to implement the solution using a programming language, then learning the second programming language is easy, so you can always learn. When I joined Twitter, I didn't know scholar, but then over the time I learned and I like it now.