This told essay is based on a conversation with Saurabh Khandelwal, a 28-year-old machine learning engineer at Meta, based in Bellevue, Washington. The following has been edited for length and clarity.
There are so many different paths in the world of AI and machine learning.
For those looking to enter this field, it’s important to be careful about how you spend your time learning. I’ve worked at both startups and big tech companies, and I’ve had to be intentional about how I represent my career. I’m currently a Machine Learning Engineer at Meta.
As technology continues to change and new models emerge, it’s important to focus on both the purpose of the work itself and how you present yourself as a difference-maker in that work.
When I applied for the role at Meta, I focused on building a consistent story on my resume. I think that helped me apply and got me closer to my long-term career goals.
I started in the startup world before joining Big Tech
My first job was as a founding machine learning engineer at a startup. Then, in the summer of 2022, I was interning as a software engineer at a hedge fund in New York and applied for a job at Amazon.
I joined Amazon in February 2023. I really enjoyed my time there. I learned a lot about how big tech approaches problem solving and scaling resources.
I was planning to close an existing project at the end of 2024, and since my role at Amazon was limited to implementation only, I wanted to move into a machine learning role with both a research and implementation focus. I started looking for opportunities and by the end of February 2025, I left Amazon and joined Meta as a Machine Learning Engineer.
Meta has more independence
My role at Meta is more closely tied to product outcomes than my job at Amazon, which is one of the reasons I was interested.
At Meta, we focus on both research and implementation. There is less emphasis on getting everyone on the team on the same page compared to my previous role at Amazon. If you think your idea is good, it’s a good idea to try it out, test it, and ship it to production with the necessary guardrails in place.
I wrote a story on my resume to get a job at Meta
When I applied for this role, I didn’t just list my projects on my resume. We focused on highlighting the details that show the strongest through lines. I wanted to tell a story.
My story had two parts. First, I worked at a startup before joining Amazon, so I understood machine learning systems as a whole. Also, the scope of tasks at a startup is much broader than at a large tech company. Since everything is built from scratch, we had to understand every process step by step and build the components accordingly.
Another part of my story was that my experience at Amazon allowed me to solve machine learning systems at scale. In my resume, I was specific about the scale I worked at, the number of tokens I processed, and the number of requests I served. Because big tech companies value systems that work at that level. Even startups care about these scaling data points because they want to operate and deploy at that level at some point.
The overall explanation was that because I understand the system end-to-end and understand the entire lifecycle of a machine learning system, I can make a significant difference in getting one idea to its final destination.
My best advice for machine learning engineers
Advances in machine learning are now so fast that it’s difficult to keep up.
If you have a little more experience in the industry, figure out what system or part of the problem you want to focus on and really follow that research. Follow bloggers, attend conferences in your field of interest, and dive deeper into those issues. I set aside a dedicated study time each week, during which I block off an hour on my calendar.
If you’re just starting your career, focus on building a strong foundation for building machine learning systems. With a good understanding of the fundamentals, these systems can be adapted and deployed even as architectures and tools change over 100 times.
Do you have a story to share about your career in technology? Contact this reporter, Agnes Applegate, at: aapplegate@businessinsider.com.
