# Anupam Samanta > Machine Learning Engineer | LLMs, NLP, Ads AI @ Google | On-Device ML (previously at Google Nest) Location: San Francisco Bay Area, United States Profile: https://flows.cv/anupam ML/AI Engineer | Search Ads @ Google Driving large-scale ML innovation, including Large Language Models, to improve query understanding at Google scale. Delivered launches with multimillion-dollar revenue impact. Previous Experience: • On-Device ML @ Google Nest – Built multimodal ML frameworks powering camera, radar, and audio-based smart device features • Software Engineer Intern @ Evernote • Software Developer (3+ years) @ Samsung & Rubique (FinTech startup) Education & Recognition: • M.S. Computer Science, Stony Brook University (GPA 3.9/4.0) • Graduate coursework: ML, Big Data, Computer Vision, Networks, Databases, Advanced Algorithms, Computational Biology • Awards: Google Research Tech Impact Award; Special mentions from Ads SVP Publications: • QUILL: Query Intent with Large Language Models Using Retrieval Augmentation and Multi-Stage Distillation – arXiv, 2022 • PROMPT: Personalized User Tag Recommendation for Social Media Photos Leveraging Personal and Social Contexts – IEEE ISM, 2016 Patents: • Method for Training Large Language Models to Perform Query Intent Classification – US Patent App. 18/491,877 (2024) • Privacy-Preserving Methods for Personalized Sound Discovery within an Environment – WO Patent WO2023224622A1 (2022) Technical Skills: Python, C++, TensorFlow, PyTorch, Mediapipe, Distributed Systems, Multimodal ML ## Work Experience ### Senior Software Engineer @ Google Jan 2021 – Present I work on the Ads Query Understanding team, where I develop state-of-the-art machine learning models and infrastructure for shopping-related ads on Google Search. As part of the query understanding team, I create ML models that capture query intent, which are used by downstream applications, including retrieval and auctions, as a prefilter to allow only commercial intent. My technical expertise includes C++, Python, and TensorFlow. Key Achievements: Innovative LLM Integration: Introduced Large Language Models (LLM) to search ads query intent, resulting in multiple successful launches that generated $0.X billion in revenue for Google. Leadership: Designed end-to-end projects, from collaborating with research teams and prototyping to establishing distillation pipelines for serving LLMs at Google scale with extremely low latency. Led a team of engineers to explore improvements in the entire pipeline, scoping work for follow-up launches, including introducing continuous distilled models, exploring different architectures in teacher and student model, feature explorations, etc. Recognitions and Awards: Received multiple accolades, including the Research Tech Impact Award and special mentions from the SVP of Ads for one of the most impactful launches of Q2 2023. Presented follow-up tech talks across Google Ads. ### Software Engineer at Google Nest @ Google Jan 2019 – Jan 2021 | Mountain View, California, United States I was part of the Google Home/Nest on-device machine learning platform team, responsible for developing end-to-end smart features across all Google Home devices (horizontal) and within individual device features (vertical). We built multimodal ML/AI features leveraging vision, audio, and radar, requiring collaboration with Research, Hardware, Frontend, and backend services. Key Projects: Sleep Sensing: Collaborated with research teams to help shape the sleep sensing project. Built end-to-end pipelines for radar preprocessing and data collection, developed heuristics for consolidating ML model predictions into sleep schedules, combined radar and audio outputs for detailed sleep summaries, and analyzed external environments affecting sleep. Also contributed to engineering productivity testing. Audio Detection: Designed the On-device Personalized Learning Sound Inference for sound discovery in personalized sound detection. Optimized the pipelines to reduce CPU workload by creating coarse audio event models and matching them to personalized events as needed. Published a patent for our work. Smart Framing: Developed active framing for participants in video calls. Worked on logging metrics for usage and prototyped improvements such as face tracking using a face-person pose detection (FPP) model in video calls. ### Graduate Teaching Assistant @ Stony Brook University Jan 2018 – Jan 2018 | Stony Brook, New York, United States CSE332: Introduction to Data Visualization ### Software Engineering Intern @ Evernote Jan 2018 – Jan 2018 | Redwood City, California • Implemented keyboard shortcuts for Evernote’s all new web platform for performing content formatting and various operations such as new note, adding tags and expanding/collapsing notes. • Implemented Quick switcher, an app wide context switcher, to quickly navigate and search within notes notebooks and workspaces, and sort them according to the most recently accessed items. • Frameworks used: ES6, Javascript, React, Redux, redux-sagas, ducks, chai-js ### Software Engineer @ Rubique Jan 2017 – Jan 2017 | Mumbai • Conceptualized, designed, developed and deployed mobile application for Rubique’s loan lending platform • Implemented major projects such as search and filter module, share and earn module, document upload section for KYC, chatbot for rubique, meeting module • Implemented entire redesign of the app along with animations and API integration with new back-end system. • Introduced coding style and standards, coding review, QA lifecycle and other industrial grade methods to the application development, to reduce project turnaround time. • Implemented several custom libraries, such as custom wrapper around volley, custom seekbar, custom collapsible calendar class, custom animation classes, etc • Technologies used: Firebase, REST API’s, Volley, Glide, etc. ### Engineer @ Samsung Electronics Jan 2014 – Jan 2017 | Noida • Worked on latest Android platform for R&D of organizer module for all flagship devices and tablets • Worked on the turbo speed technology in J210F, rewrote the entire clocks application using Google’s code base following Samsung UX/UI to achieve 40% faster performance with 10% space efficiency . • Worked in Samsung HQ, South Korea, to handle the project development for clock application in Tab E(T561). • Rewrote and improved audio focus and flash focus (for visually impaired) of Alarm and Timer module to better handle interaction with other system applications. ## Education ### Master of Science - MS in Computer Science Stony Brook University Jan 2017 – Jan 2018 ### Bachelor’s Degree in Computer Science Indian Institute of Technology (Indian School of Mines), Dhanbad Jan 2010 – Jan 2014 ### High School in Physics, Chemistry Maths and Computer Science Jawahar Vidya Mandir, Shyamali, Ranchi Jan 2009 – Jan 2010 ## Contact & Social - LinkedIn: https://linkedin.com/in/anupam-samanta --- Source: https://flows.cv/anupam JSON Resume: https://flows.cv/anupam/resume.json Last updated: 2026-03-22