When people hear Machine Learning Engineer, most people think of something along the lines of a mechanical engineer or maybe a machine operator, but it’s actually a mix between a computer scientist and a data scientist. A Machine Learning Engineer is someone who automates machine learning models and develops processes and tools to implement and maintain those models in production. If you’re not familiar with machine learning, they’re mathematical algorithms that learn from historical data to make predictions or recommendations on new data. Netflix’s recommendation model to suggest new shows and movies based on your viewing history is a great example.
A typical day for me begins when the wife and kids leave the house.. I work exclusively from home, so the workday begins on my schedule. I really enjoy the flexibility and not being tied to a typical 9-5 window. I usually check emails and chats for anything I missed from the previous day and then get into my tasks. These range writing code, documenting standards, and giving presentations to leadership. I work pretty frequently with data scientists, to help them get their models ready for implementation. Thankfully, I don’t have many meetings a week and have a lot of control in setting the pace of my workload.
Working in healthcare as an IT professional has been really interesting. A lot of the work I support directly impacts patients, which is really cool. Most of the models I implement help identify high-risk patients for things like emergency room visits or developing certain conditions, and then interventions are designed to assist those patients. Healthcare has probably been the slowest industry to adapt to data science and data-driven methodologies, but it’s made a lot of progress in the past few years.
Overall, I enjoy being a Machine Learning Engineer. High compensation, remote work, and autonomy makes it pretty hard to beat for a corporate job. If you’re interesting in this career path, I’d recommend getting a undergrad and graduate degree in computer science or applied mathematics and working for a few years as a data scientist.
Â
