“Bridging the gap between PhD and SWE” would be a good subtitle for my career.

I started out writing software for scientists, psychologists, first at a university, then a small company. After eight years of that I went to grad school and got a PhD in CS (ML/AI), and did a postdoc, before going into industry, and eventually landed a role in what was then called “data mining”, later “data science”, then “machine learning engineering”. In the beginning when the team was small, we were all generalists, doing both the science work and the engineering. As we grew, specialized roles developed, but I was able to chart a course somewhere between a SWE and a scientist, doing a lot of knowledge work, experiments, measurement, and presentation, but also building common tools that the rest of the team can use.

I’ve been out of the job market for 15 years now, but I think any company that does science and builds software would value your skillset. In fact, when I was shifting from academia to industry, I started out determined to be a “scientist”. After all, what was my PhD for, anyway? But my SWE chops were pretty evident on my resume, and I had a hard time getting traction. Then I got brought in for an interview at a company that had a team of scientists and a team of engineers and they brought me in for a split interview with both teams. It was clear by the end that they wanted me as an engineer, but I was insistent on wanting to be a scientist. They didn’t offer me a job, and I was disappointed. The disappointment was educational for me, and I rewrote my resume to put more emphasis on my SWE skills, and that made it easier to find a role that fit me.