I’m a Senior Machine Learning Engineer at Google, building on-device AI features for Android — including Scam Guard (real-time scam detection via an on-device Gemini model) and New Generation Call Screen. My technical interests centre on LLMs, Recommender Systems and efficient model training.

Before Google I worked at LinkedIn on AI foundations for recommendation and language models, mainly exploring techniques for fast and efficient large-batch training. I did my Master’s at NYU Courant, where I worked with Prof. Brenden Lake on modelling infant cognitive development using self-supervised deep learning — work published at NeurIPS 2020.

Experience & Education

2024 –

Google

Senior Machine Learning Engineer · Mountain View

• Building on-device AI features for Android’s Dialer app: Scam Guard (real-time scam detection via on-device Gemini) and New Generation Call Screen.
• End-to-end LLM model development: synthetic data generation, labelling, LoRA fine-tuning, and quantization for on-device deployment.
• Leading a research reading group on LLMs, fine-tuning, and quantization.

2022 – 2023

LinkedIn

Applied Scientist · Sunnyvale

• Developed foundational techniques that could be applied to Personalization and Language Models throughout LinkedIn.
• Improved training speed and AUC for Feeds and Ads models via gradient norm clipping, XLA, and mixed-precision training.
• Built an Explore-Exploit framework using Thompson Sampling over neural network output variance for recommendation diversity.

2021

Amazon

Applied Scientist · Seattle

• Causal Inference to quantify long-term downstream impact of seller actions (sponsored ads, inventory restocking) on revenue.

2018 – 2020

New York University — Courant Institute

M.S. Computer Science · GPA 3.97 / 4.0

Research Assistant · Human & Machine Learning Lab

• Noteworthy Coursework: Machine Learning (David Rosenberg), Computer Vision (Rob Fergus), Deep Learning (Yann LeCun).
• Worked with Prof. Brenden Lake on modelling cognitive development in infants using self-supervised deep learning.
• Published at NeurIPS 2020; covered by New Scientist and Digital Trends.

2014 – 2017

Amazon

Software Development Engineer · Bangalore

• Built consumer website products end-to-end (frontend, service-layer and databases).
• Later joined a 3P Ads team for revenue optimization and big data analytics.

2010 – 2014

DA-IICT, Gujarat

B.Tech. Computer Science · GPA 8.0 / 10

• Noteworthy Coursework: Computer Architecture, Operating Systems, Data Structures, Algorithms.

Publications