Alum Spotlight: Shashank Maiya, Machine Learning EngineerBy: Springboard
At Springboard, we help place students in the jobs they want. Our Machine Learning Engineering Career Track is designed to place people into machine learning engineering roles. We caught up with Shashank Maiya, a graduate of one of our career tracks, who leveraged his experience with us - the personalized mentorship from different experts and a proven career services team - to land a machine learning engineering role.
1. What's your current role?
The company I'm working for is ServiceNow. It's a software company that provides a platformized, account-based solution for identification. It's a cloud-based SaaS company: I joined as a machine learning engineer when there were 20-30 people on the team. I'm part of the natural language team. The product we work on is trying to understand SQL-like queries and translate natural language to SQL queries, so that when users want to get data, they are presented with an easier and more intuitive way to do so.
2. How did you find your Springboard experience?
It was pretty good. Springboard helped me get my resume totally centered around machine learning. I was in a totally different area before, as a systems engineer at Qualcomm, and didn't know how to build a profile around machine learning and data science -- the 6-8 months of Springboard training gave me everything I needed to fill my resume with machine learning content and projects. There were quite a few projects and a capstone that I was able to provide as evidence of my skills during interviews. Most of my CV at that time was what I learned from Springboard and it helped significantly.
My learning experience with Springboard was great, and the support from my mentor and career coaches was good and consistent -- exactly what I needed to land a machine learning job.
3. What was the job search like?
Four months into the Springboard curriculum, I started applying for jobs. I'd send my resume and profile over to the Springboard team for review, and my mentor was able to help me with different job tips. I started seriously applying to jobs close to the completion of my second capstone project. The job hunt after that took about four months; the first few months were a learning experience, but once everything came into place (thanks to the support of the career coaching team at Springboard and the experience I acquired in my course), a job offer soon came. I'm happy to be working at ServiceNow.
4. What advice would you give to people looking for machine learning jobs?
I got a lot of data structure questions during interviews. Interviews for machine learning engineer roles are quite different from interviews for data science roles, which may not focus as much on data structure or coding competency. The job I work at now involves a nuanced understanding of data structures. I had to practice coding and study data structures a lot for the technical part, even though the Springboard curriculum helped. I would normally suggest practicing with 100-150 coding questions to prepare for an interview. You should also be open to jobs at companies that aren't your dream destinations. Start with companies that are growing and looking to establish themselves -- there's always time to build your skills there.
If you want to build your own profile and skills with a proven approach to getting machine learning jobs, look no further than Springboard's Machine Learning Engineering Career Track. With guidance from our career services team, we're positive that you'll find a job within six months of graduating. But if you don't, we'll refund your tuition. (We've successfully placed hundreds of students in our Data Science Career Track and have yet to issue a refund.)
This post was sponsored by Springboard. To learn more about Springboard.com, or check out their reviews on SwitchUp.