
Vashisht Madhavan
Studied at University of California, Berkeley
Works at Amazon
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Work Experience

Senior Applied Scientist
Amazon
January 2025 - Present
At Amazon, I'm an AI researcher working on LLMs for coding. I've been responsible for helping post-train our latest model release, Nova 2 Pro. My focus is on improving how these models reason and write code through reinforcement learning.
AI Researcher
Pika
January 2024 - January 2025
At Pika, I was a researcher working on the company's generative AI models for video. I led data curation for large-scale pretraining and owned much of the post-training stack. That work powered a range of user-facing fine-tunes like Pikaffects, and I also fine-tuned multimodal LLMs for video captioning, categorization, and retrieval.
Co-Founder & CTO
Humanlike
May 2023 - December 2023
At Humanlike (YC S23), which I co-founded and ran as CTO, I built low-latency, realistic AI voice agents that automate business phone calls using LLMs and generative speech models. I led engineering and product end to end, from the first prototype to landing enterprise customers. We went through the YCominbator S23 batch.

Staff Machine Learning Engineer
Snorkel AI
July 2021 - May 2023
At Snorkel AI, I was a staff ML engineer and tech lead for the structured-documents product, which let enterprises extract, label, and classify data from PDFs and other documents. I brought foundation-model workflows into the platform — embedding search, prompt-based labeling, and LLM fine-tuning with document-specific models like LayoutLM — alongside integrations with Snowflake, Azure, and Databricks.

AI Researcher
Uber
May 2017 - November 2019
At Uber, I was a research scientist in Uber AI Labs, the company's artificial-intelligence research group. I worked on reinforcement learning and computer vision, specifically for self-driving cars and to optimize Uber Freight surge pricing. Was also involved in building an AI customer service agent that saved the company tens of millions of dollars annually.
Education

University of California, Berkeley
Master of Science (M.S.), Electrical Engineering and Computer Science
2016 - 2017
AI and Machine Learning. Focus on computer vision and reinforcement learning

University of California, Berkeley
Bachelor of Science (B.S.), Electrical Engineering and Computer Science
2012 - 2016