Smriti Singh

Machine Learning Research Engineer @Zacks Investment Research

Mountain View, CA, US
MOBILE NUMBERS
+91 *********19

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WORK HISTORY

Apr 2025 — Present

Machine Learning Research Engineer @Zacks Investment Research

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Chicago, IL, US

As a Machine Learning Research Engineer at Zacks Investment Research, my focus is on developing models that push generative AI to the forefront of the Fintech sector.

EDUCATION

N/A

The University of Texas at Austin

Master's degree, Computer Science

2012 — 2016

Delhi Public School - India

10th Grade

2018 — 2022

Manipal Institute of Technology

Bachelor of Technology - BTech, Information Technology

2016 — 2018

FIITJEE

12th Grade, Mathematics, Physics, Chemistry

ABOUT SMRITI SINGH

I’m a Machine Learning Research Engineer working at the intersection of generative AI, NLP, and ethical AI, with growing interest in how these technologies can shape the future of finance. My work centers on building AI systems that are not only powerful, but also trustworthy, reliable, and human-centered.I earned my M.S. in Computer Science from The University of Texas at Austin, where my research focused on how large language models perceive emotions and social nuance. My publications have appeared at leading venues (ACL, NAACL, COLING), covering topics such as debiasing embeddings and multimodal bias detection. It is my honor to have had some of this work featured in the New Scientist and highlighted in UT Austin’s Newsletter.In industry, I’ve worked on projects that bring cutting-edge generative AI into production, working across technical and non-technical teams to create systems that meet complex, real-world needs. I thrive on translating emerging research into solutions that balance innovation, fairness, and impact.Outside of research and engineering, I’m passionate about mentorship, community, and communication. I’ve spoken at PyData Global and FruitPunch AI, and I’m always open to relevant public speaking/mentoring opportunities around AI, ethics, fairness, safety, women in AI/ML and applied machine learning. If any of these topics seem interesting to you, feel free to drop a DM:)

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