Abishek Sridhar

Gemini Post Training & Evals @ Google | Ex-Snowflake | CMU | IITM

Cupertino, California, United States

About

Working in the Applied ML team at Snowflake. Graduated from Carnegie Mellon University as part of the MS in Computer Science ‘23 cohort. Completed my undergraduate in Electrical Engineering at IIT Madras with a minor in Computer Science as the topper of my department. I love problem-solving, computer science, and mathematics, and deeply passionate about Algorithms, Machine learning and Deep learning. I am interested in quantitative finance as well, enjoy challenges, and coming up with ingenious, innovative solutions. Last but not the least, coding is fun and I am fun loving.

Experience

  • Research Engineer at Google
    Jul 2025 - Present · 1 yr 1 mo

    Doing my part to bridge the real-world gaps in Gemini at deep research and long horizon tasks

  • Software Engineer (Machine Learning) at Snowflake
    Feb 2024 - Jul 2025 · 1 yr 6 mos

    • Worked on semantic SQL generation and routing in Cortex Analyst Text2SQL agentic system • Shipped AI Text Classify, which consistently fared within the top 2 revenue in 2023-2024

  • Graduate Teaching Assistant at Carnegie Mellon University
    Aug 2023 - Dec 2023 · 5 mos

    TA for course 10-605: Machine Learning for Large Datasets from the ML Department

  • Graduate Research Assistant at Carnegie Mellon University - School of Computer Science - Language Technologies Institute
    Jan 2023 - Dec 2023 · 1 yr

    Worked under Prof. Graham Neubig on building LLM agents and WebArena: A realistic and reproducible benchmark for web navigating agents, published in ICLR ‘24

  • Software Engineer (Machine Learning) Intern at Snowflake
    May 2023 - Aug 2023 · 4 mos

    Part of the Applied Machine Learning Team - • Researched on obtaining semantically meaningful row embeddings using deep models for heterogenous structured tables. • Proposed novel self-supervised pretraining of tabular transformers, with embeddings achieving SoTA performance on unsupervised anomaly detection.