
I am a computer scientist and engineer focused on finding and solving meaningful non-trivial problems at the intersection of research and application. I love building things from zero to one and prefer working with like-minded mission-driven people who care deeply about the societal impact of their work.
Background
I have extensive experience building and scaling end-to-end machine learning models.
Currently, I am working at Writer, where I lead the development of a next-generation multimodal, agentic, vision-based information retrieval system to enable accurate natural language QA across complex content, including text, images, tables, charts, equations, video, and audio.
Prior to Writer, I was a Staff Machine Learning Engineer at Shopify, where I led applied research on LLMs and information retrieval for e-commerce.
Before Shopify, I was a founding member of the Artificial Intelligence group at HubSpot, where I rose to become the most senior IC MLE and helped grow the team from 5 to XX+ members.
I studied computer science and business at Rensselaer Polytechnic Institute, where I spent most of my time competing in hackathons and conducting research on free-space optical communication (FSO) to enable radically higher-bandwidth interplanetary communication. I then went to Georgia Tech and obtained a masters in computer science with a concentration in machine learning.
In my free time, I enjoy reading, writing, sailing, using Notion as my second brain, and engaging with all things automotive. I also dabble a bit in filmmaking and photography.
Select writing
Blog: Dear SWE, ChatGPT Whisperer, and aspiring MLE - 2024
HubSpot: Doing More with Less - 2020
Talks
Boston Machine Learning, August 2018: Machine Learning & Email Anti-Abuse
Contact
You can find me on Twitter @MukulSurajiwale, as therealmukul on Github, or here on LinkedIn.
Sometimes I also write out my thoughts in long-form, which can be found on my blog.
I am based in the NYC and I love meeting new people. So if you want to grab a coffee, I'd more likely than not, be down.