A 23-year-old machine learning engineer joined Meta in June after leaving Amazon, drawn by Meta's AI projects and a recruiter outreach. The engineer began a master's program in 2022 amid the rise of ChatGPT and notes that AI advances have intensified competition for roles. The engineer completed undergraduate studies in one year using high-school credits, worked full-time while pursuing a master's in AI, and spent nine months at Amazon. The engineer accepted a Meta offer with total compensation over $400,000. Machine learning job titles and responsibilities vary across companies and commonly blend research and implementation.
This as-told-to essay is based on a conversation with Manoj Tumu, a 23-year-old machine learning engineer at Meta based in Menlo Park. It's been edited for length and clarity. Business Insider has verified Tumu's salary and employment. Machine learning has gone mainstream. I started my master's program in 2022, around the time ChatGPT was released. The advancement of AI and AI tools has made it a very competitive field, and many people are trying to get in.
It took me one year to get my undergraduate degree because I had college credits from classes I took in high school. Then I worked full-time as an engineer while doing my master's in AI. After my master's, I landed a role at Amazon, where I worked for nine months as a machine learning software engineer. While I was at Amazon, I saw Meta doing a ton of cool machine learning things. When interesting roles came up, I just applied on their website or LinkedIn.
Here's my advice for trying to break into this field. Understand machine learning and its shifts One of the things about machine learning roles is that there's a lot of variation in the title. Depending on the company, it could be a research scientist, applied scientist, software engineer, or machine learning engineer. At Meta, I'm a machine learning software engineer on an advertising research team.
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