Shyam Padia ⚡️
Profile
Senior Software Engineer with 6+ years of experience specializing in AI/ML, large-scale distributed systems, and personalization platforms. Expert in leveraging Generative AI, machine learning, and big data technologies to build scalable solutions that drive business impact. Passionate about robotics, automation, and infrastructure engineering with a proven track record of leading cross-functional teams and delivering innovative products that generate millions in revenue and significantly improve operational efficiency.
Education

Master of Science in Computer Science

Sept 2017 to Dec 2019 at Northeastern University, Khoury CCIS, Boston, MA | GPA: 3.2/4

Courses: NLP, Reinforcement Learning, Robotics, Machine Learning, Artificial Intelligence

Bachelor of Engineering in Computer Engineering

Aug 2012 to June 2016 at University of Mumbai, Fr. CRCE, Mumbai, India | GPA: 7.4/10

Experience

Senior Software Engineer - Personalization at Intuit

From Jan 2025 to Present at Mountain View, California

  • Architected unified user profiles integrating third-party data with ML embedding models for similarity-based offer recommendations using Python and vector databases
  • Led cross-functional team of 6 engineers developing AI marketing agent using Symphony and LangChain to automate content generation and campaign deployment, accelerating go-live time by 90%
  • Managed team of 5 engineers delivering bulk content creation system with dynamic templates and audience segmentation, increasing content production capacity by 1400%
  • Designed and deployed AI powered content generation pipeline using LLMs to automate end-to-end marketing workflows, improving time-to-market by 75%
  • Developed comprehensive AI strategy roadmap for personalization featuring intelligent content recommendations, predictive analytics and workflow automation

    • Software Engineer 2 - Personalization at Intuit

    From Jan 2021 to Jan 2025 at Mountain View, California

  • Developed RAG-based AI assistant using Generative AI, Hugging Face transformers and LangChain for automated marketing content generation, reducing customer churn and accelerating campaign authoring workflows
  • Engineered self-service analytics platform processing clickstream data with PySpark and AWS EMR, building React dashboards that reduced production incidents by 40% and increased marketer productivity by 50%
  • Designed scalable data entities using PySpark enabling real-time multi-source data ingestion, eliminating schema approval bottlenecks
  • Implemented AWS Personalize machine learning recommendation system on clickstream data, improving personalization quality and reducing API latency by 20%
  • Built real-time Kafka event streaming pipeline integrated with Customer Data Platform with RBAC and approval workflows, generating $10M incremental revenue through dynamic audience targeting
  • Trained and deployed XGBoost and Deep Neural Network models for predictive business health scoring, reducing investment risk by 23%

    • Software Engineer 1 - QuickBooks at Intuit

    From Jan 2020 to Jan 2021 at Mountain View, California

  • Implemented parallelized automated testing framework using Cypress for synthetic monitoring, preventing $10M potential revenue loss and ensuring pricing accuracy across platform
  • Developed machine learning models using XGBoost and Neural Networks for business health prediction, achieving 12% accuracy improvement over baseline models
  • Built predictive revenue forecasting model leveraging customer behavior simulations to estimate revenue impact from dynamic pricing strategies
  • Engineered automated customer segmentation pipeline using AWS Glue, Pandas and SQL to identify eligible cohorts for targeted pricing campaigns
  • Developed full-stack pricing management platform using React, Spring Boot and AWS for offer configuration, price simulation and campaign execution, delivering $20M cost savings and increasing operational efficiency by 50%

    • Software Engineer Intern - TurboTax at Intuit

    From May 2019 to Aug 2019 at San Diego, California

  • Developed OCR-based document processing feature for W2 form upload in TurboTax onboarding flow, reducing customer tax preparation time by 20%
  • Integrated machine learning Decision Engine for natural language intent classification, replacing third-party API and reducing response latency by 30%

    • Software Engineer Co-op - TurboTax at Intuit

    From May 2018 to Dec 2018 at San Diego, California

  • Engineered case deduplication microservice for customer support portal using machine learning algorithms, improving response time by 45% and reducing duplicate cases by 7%
  • Developed dynamic Smart Fields component using React and PHP backend to automate content publishing workflows, reducing deployment time by 30 minutes and decreasing support case volume by 10%
  • Architected serverless URL redirect service using AWS Lambda, API Gateway and DynamoDB, improving routing efficiency by 35%

    • Software Developer at VoterCircle

    From Nov 2016 to May 2017 at Bangalore, India

  • Developed distributed campaign management platform using Meteor.js and Angular framework, increasing canvassing operational efficiency and voter turnout by 15%
  • Implemented ElasticSearch-powered contact matching algorithm integrating voter registration data with social media profiles, improving outreach effectiveness by 10%

    • Projects

    NixOS Infrastructure Cluster - Declarative Homelab Platform

    June 2025

    Architected highly available NixOS-based homelab cluster with declarative infrastructure-as-code using Nix Flakes, deploying several self-hosted services such as n8n, Nextcloud, Home Assistant, Immich and OpenWebUI with automated rollbacks and zero-downtime updates

    Lumino Lab - Distributed Kubernetes Home Server

    Dec 2024

    Designed hybrid homelab infrastructure using N100 mini PCs and Raspberry Pi cluster orchestrated with Kubernetes, integrating Proxmox virtualization, UnifiOS, Open Media Vault and Home Assistant with secure Tailscale mesh VPN and Cloudflare DNS

    Omnidirectional Autonomous Robot with Computer Vision

    Jun 2024

    Engineered omnidirectional Raspberry Pi robot with servo-controlled 6-DOF robotic arm implementing inverse kinematics, OpenCV object detection, speech-to-text voice commands and autonomous navigation with obstacle avoidance

    Reinforcement Learning Transfer for Robotic Manipulation

    Oct 2019

    Evaluated transfer learning effectiveness for robot arm simulation using PyTorch and OpenAI Gym, comparing Q-Learning, DQN, Policy Gradient and MCMC algorithms, achieving 35% faster convergence and 28% improved task performance

    Multi-Track Music Generation with Transformer Architecture

    Apr 2019

    Developed novel multi-transformer neural architecture for polyphonic music generation with separate models for melody, bass, drums and harmony using custom global multi-headed attention, improving musical coherence by 45%

    Paragraph Embedding Generation using Variational Autoencoders

    Apr 2018

    Implemented deep learning architectures in TensorFlow for unsupervised paragraph representation learning using VAE and bidirectional LSTM Seq2Seq models on Gutenberg Corpus, achieving 22% improvement in semantic similarity tasks

    Certifications
    Open Source Contributions
    • Vicinae - Desktop Application Launcher (2025): Contributed features to high-performance desktop launcher built with C++ and Qt, implementing Raycast-compatible extension APIs, TypeScript SDK integration and Linux-native keyboard-driven productivity tools
    • Mopidy - Python Music Server (2024): Contributed features and bug fixes to extensible music server, implementing Spotify integration enhancements, playlist synchronization improvements and audio stream optimization for Raspberry Pi deployments
    Technical Skills
    Languages: Python, Java, JavaScript, TypeScript, Nix, Lua, SQL, Scala, Go, C/C++
    ML/AI: PyTorch, TensorFlow, Hugging Face, LangChain, OpenCV, Vespa, NLTK, ScikitLearn, Keras, Gensim
    Frameworks: Spring Boot, React.js, HTMX, Django, Node.js, REST, gRPC, Microservices
    Big Data: PySpark, Kafka, Hadoop, Pandas, PyArrow, Hive, EventBus, RabbitMQ
    Cloud: AWS (SageMaker, Lambda, Glue, Personalize, EMR, OpenSearch, Athena, Redshift), Docker, Kubernetes
    Databases: PostgreSQL, DynamoDB, MySQL, SQLite, MongoDB, Redis, ElasticSearch, Vector Databases