Advance your Career with Automattic Rotations

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One distinguishing feature of Automattic’s work culture is a team rotation, through which an individual can move from one team to another. A rotation can happen for a few reasons: to “try out” a new role and gain new skills, to backfill an understaffed team, or to cultivate cross-pollination and diversity across the company. Some rotations are several months long, while others may turn into a permanent team switch.

Tumblr, which is part of Automattic, is currently hiring data scientists and search engineers and machine learning engineers. Thanks to this system of rotations, last year we were able to fill a few of these positions, on the Tumblr Core Data Science team, internally. This team contributes to Tumblr recommendation systems, discovery feeds, targeted push notifications, user-interest profiling, and computational advertisement. Team members work on designing, developing, and maintaining large-scale machine learning algorithms, data pipelines, and backend services to connect users with the content they love. Our data infrastructure is built on top of open source big data frameworks such as Apache Spark and Scalding, orchestrated by Apache Airflow and with a PHP backend layer. 

In this post, Adam and Vicki, two Automatticians who experienced a rotation onto the team, tell us about their work in data, their rotations, and being part of Automattic. 

Tell us about your background in data

Vicki: I started out as an economics major because I wanted to work with both words and data. In one interview early in my career, I actually stated that my dream job was a journalist for The Economist because I could do both econometrics and written analysis of complex world issues. My first job was as a data analyst, and it turned out that you can’t do complex analysis without programming, so I became interested in SAS and R, the two popular statistical languages at the time.

From there, I started working with Python and Hadoop, and became really interested in data science, which was a brand-new field at the time — although with a lot of prior history from analytics and database management and engineering :).

I’ve since been working in data science, and most recently, engineering, for the last six years, including a lot of time spent consulting with Fortune 500 companies on what their data pipelines, ML ops, and modeling systems should look like.

When I came to Automattic, it was in a lot of ways like closing the loop on my Economist dreams, because I get to do a lot of writing, as well as a ton of engineering and analysis to make the writing happen.

Adam: Data has been in my mind since primary school. Ten-year-old me asked my dad about a book he was reading. The title on the cover said Neural Networks. He said it was a manual for making computers smart, just like Transformers. How cool was that?! Too bad I didn’t know any linear algebra at the time. I thought “computers must be interesting” and went off to play with Legos. 

A few years later, I found that same creative joy of Legos in learning HTML. By the time I finished high school, I was already a freelance web developer. Along the way, I learned Python and SQL. Eventually, I got involved with government projects, San Francisco startups, and fundraising for my own products.

But then I realized that computers had already become smart, just like my dad told me. I could have a conversation with my phone while my car was driving me to an automated grocery store. Transformers were clearly just a matter of time now. The only problem was I had no idea how any of that worked!

I caught up with mathematics through MIT OCW, did a bunch of courses, and concluded with Stanford’s AI professional program. I now understood more, which was good, but I wasn’t sure what to do next.

It all came together when I joined Automattic. I had space to build my data muscles while growing as a software engineer. Eventually, I was ready for a rotation in the Tumblr Core Data Science team. 

Tell us about your rotation

Vicki: In February, my team, which was previously working on platform experience at, started a rotation on Tumblr, working side by side with the content discovery and recommendations teams there. I enjoyed the rotation so much, and the set of problems we’re working with at Tumblr with respect to data and machine learning and the user experience, that I decided to stay. For more about what I do, check out this recent interview.

One thing that has really struck me about Automattic is the flexibility and fluidity here: teams are constantly in flux and people move around based on the needs of the company and the preferences of the individual. We hire people based on strong engineering fit as opposed to specific job titles within divisions. As Anne wrote in this wonderful post about Automattic culture, this means that you may not work on a single focus for years — although some do — and that the team you’re on will likely evolve.

Adam: At Tumblr, I worked with content recommendations. Our goal was to connect users with fascinating writeups, art, and videos. To get there, we read white papers, debated equations, and tried different models. My favorite part was pondering unexpected philosophical questions: What does it mean for two things to be similar? What makes a piece of content interesting? How do you define high quality?

Getting up to speed was like climbing a challenging mountain: exhausting but deeply fulfilling. The scientific rigor was as strong as at Stanford, and for a good reason: projects can take a long time. A wrong assumption or a formula early on may cost you months of delays. Caring about the details pays off. In web apps, many ideas may be roughly prototyped in a day or a week. In data, a day is how long you wait for the results of a database query.

Unlike Vicki, I returned to my previous team after my rotation.  Three years into my data journey, I realized my motivation for pursuing a career in data was more of “I should” than “I want to.” It was a difficult realization, but a liberating one, and it allowed me to listen to my heart — which was with the WordPress community.

What do you enjoy about working on various products in the Automattic ecosystem?

Vicki: I really enjoy the scale and impact that we have around shared written communication, in a positive way. One of the things I love is how we dogfood the act of blogging, in the form of internal blogs called P2s.

Often, there are conversations around how social networks negatively impact our world today, and for good reason. I like working on social products whose mission is to democratize publishing, making the world wide web slightly better, and with a focus on open source. For me, that’s  Tumblr, where you can freely post and find creative content —  and now support creators — or WordPress, which empowers both bloggers and entrepreneurs to realize their ideas. There is a lot of positive potential in this ecosystem, and I’m excited to be a part of it.

Adam: Besides the impact that Vicki covered so well, I enjoy three things: safety, growth, and friendships.

Safety, because I don’t have to worry about sending the wrong message. When I share my passions, people smile and help me pursue them at Automattic.

Growth, because even after 15 years in the industry, I keep learning new things. Every product is a new challenge, every team has a unique perspective, and every day feels fresh. It works both ways, too: during my Tumblr rotation we were building a REST API, and I brought in a lot of relevant experience to the table.

Friendships, because I often get to meet fantastic people, have insightful conversations with them, and then stay in touch long after our work is finished. 

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