WWCode Conversations 49: Priyanka Vergadia Staffing Developer Advocate at Google
Written by WWCode HQ
Women Who Code Conversations 49 | Spotify — iTunes — Google — YouTube — Podcast Page
Stephanie Rideout, Leadership Fellow at Women Who Code for the Python Track, interviews Priyanka Vergadia, Staff Developer Advocate at Google. They discuss the power of being a generalist when working in technology, the benefits of Cloud for machine learning, and Priyanka’s passion for color and visual storytelling.
Stephanie Rideout, Leadership Fellow at Women Who Code for the Python track, interviews Priyanka Vergadia, Staff Developer Advocate at Google. They discuss the power of being a generalist when working in technology, the benefits of Cloud for machine learning, and Priyanka’s passion for color and visual storytelling.
Can you share a little bit about your career journey?
I have basically taken the traditional path. I started off as a software engineer in Test. There were sales engineering teams that used to sit very close to me when I was writing software development testing code. It gave me a little peek into what they do. I expressed my interest in trying that out. I realized that I’m really good at presenting technical concepts to businesses, as well as technical folks. I also explored building and creating videos and visual storytelling, bringing technical concepts and telling them in interesting ways so that they are easier and faster to learn. Currently, I am a staff developer advocate at Google Cloud.
Tell us about working at Google and the work you do there as a staff developer advocate?
Working at Google was a dream for me. When I started in 2017, I definitely had imposter syndrome. My whole focus was to learn from the folks around me and develop myself technically, as well as professionally. I was also in the process of finding what I love, which is a constant journey for everybody. I found this path of visual storytelling and learning and teaching at the same time, which is what the whole developer advocacy job is. The culture and the team allow you to progress in the direction that you are really good at and let that shine with the goals of the team, which I really enjoy.
What is visual storytelling and how does your passion for storytelling help you to create technical content that best serves the developers you work with at Google?
I just got my book published. I have a passion for colors and visuals. That’s how I learn things. As I was learning Google Cloud, I thought it would be great to have visual references for each of the different products. Not just about Google Cloud, but also cloud in general. When I looked for resources, there was not much out there to learn visually. That’s how the book was born. It’s written in a way that you don’t have to read the whole book, you can just sit down for 10 minutes and read two pages and consume that. It’s connected if you read end-to-end, but it’s also enough to use as reference.
What excites you most right now about the intersection between cloud computing and machine learning?
Cloud computing is the enabler for machine learning. And machine learning has a lot of things that a data scientist or an ML engineer needs to do. A part of that is building models and training those models. The second big part of machine learning is serving those models. Cloud has the potential to help expedite machine-learning model training. Now, when you’re training the models as a data scientist or as an ML engineer, you just want to build the model and train and get the output of that model.
Cloud computing really helps facilitate the growth of those machine-learning projects and models serving those models. If I build a model and I think that four people are going to utilize it, and there’ll be maybe 400 requests coming to it, but then tomorrow 4 million people hit that model, you need to have that scale automatically for the serving of your model. Cloud has all the tools that allow you to do that. That’s where that intersection is for facilitating and making it easier for machine-learning engineers and data scientists to do their job and not have to worry about some of the compute and infrastructure-related items.
Can you share about the power of being a generalist in tech?
For me, the choice of being a generalist was very clear because I can go deep into topics, but my real passion lies in learning a bunch of different topics. That’s where I get motivated, I get excited about learning a new thing every day. I enjoy the diversity of the work each day with different customers.
What are you passionate about outside of work?
I am introverted at heart, so every time that I have a little bit of downtime outside of work, you’ll definitely find me either sketching or painting or just chilling in that way. Also, I just got a puppy, he’s about eight months old, so he’s taking up all the time right now.
What is a pro tip you would like to share?
Be open to saying ‘yes’ to things. Especially early on in the career, it is so important to say ‘yes’ because you want to open yourself up to different areas, your mind up to different areas and fields that you might not know about. Network with people who you know what they do but you want to learn more to see if you want to try something out in that direction. A minor tip is knowing what you don’t like. Those are the two tips that have really worked for me.