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5+ years building production ML systems in e-commerce and B2B SaaS. I own the full stack from problem framing and data to type-safe pipelines, models, and experiments in production. I care about robust, observable ML infrastructure that moves product metrics.
Areas of Interest
Key Skills
Machine Learning & AI
Cloud & Infrastructure
Data Engineering & Analytics
Web Development & Design
Programming & Development
Work Experience
Aidaptive by JarvisML
Cupertino, USAAI-driven personalization platform focusing on hospitality and e-commerce.
Senior ML Engineer
Dynamic Pricing System - Twiddy VRM
Architected an ML-based dynamic pricing engine managing $475M+ in bookings for 1,240 vacation rental properties, with experiments indicating $5M+ annual revenue upside from optimized pricing.
Modeled demand and price elasticity with XGBoost over 60+ engineered features (GA4 demand signals, image-derived attributes, seasonal/geo elasticity, occupancy and booking lags), with features materialized in BigQuery.
Featured Image Reranking System
Built an ML-based image reranking system deployed on 49M+ impressions, increasing CTR from ~0.5% → 9% (18× uplift, 53% A/B test win rate).
Optimized real-time inference latency by extending Flagr in Go, with monitoring and telemetry.
Image Attribute Extraction - Cross-Client
Achieved F1 ≈ 0.9 on 100+ hierarchical attributes by batch-processing 200K+ images across 8 clients.
Integrated Gemini Vision and Claude for zero-shot attribute extraction.
ML Infrastructure Library (ml-lib)
Designed and shipped a company-wide ML infrastructure library and model registry (Vertex AI + BigQuery + internal services) that became the default backend for new ML features across vision and LLM workloads.
NL→SQL Service "Ask a Metric"
Shipped an NL→SQL service with a Faiss vector store and result cache; reduced median response latency by matching queries and cut LLM costs 90%.
Developed a visual similarity recommender that increased RPI by 14% for select clients by surfacing higher-value alternative products.
Built an internal GenAI experimentation framework using LoRA-based fine-tuning (LLMs / SDXL) to generate ad copy and creatives with consistent characters.
Subway India
Bangalore, IndiaQuick-service restaurant franchise with 1,000+ stores across India.
Independent Contractor
Delivered enterprise support platform via WhatsApp for Subway India with 1,065 stores (81% adoption) across India, processing 11K tickets (362K+ messages) with 56% sub-2-minute resolution (51-min median) through decision tree routing across 13 departments, laying foundation for ML-powered ticket routing.
Architected platform serving both franchise support and employee innovation (Sankalp) with HR/committee governance through 4-tier RBAC, event-driven state machines, JWT/OTP/SSO auth, WhatsApp Cloud API integration, serverless deployment with PostgreSQL and Redis.
Aisle3
London, UKEarly-stage e-commerce aggregator for multi-merchant product discovery.
Founding ML Engineer
Multi-modal Product Matching Engine
First ML hire; owned the end-to-end design, training, and deployment of a multi-modal product matching engine (text + image) for noisy, long-tail e-commerce catalogs using Swin Transformers and self-supervised pretraining (DINO, SimCLR, MoCo), reaching P@1 ~0.9, Recall ~0.96 on a curated hard evaluation set.
Built a serverless, parallel, fault-tolerant workflow on AWS Step Functions (training → vector indexing → clustering → product groups), reducing infrastructure costs by ~60%.
Built a web-based active learning annotation tool that generated 120K+ pairwise labels via human-in-the-loop review and targeted sampling, significantly accelerating training data collection.
Online Vector Search Platform
Deployed a Faiss + Elasticsearch vector search platform (orchestrated with Airflow) processing 60GB+ / day, cutting duplicate listings by ~90% and powering features like product matching, color detection, and image-attribute extraction.
Early Work(May '19 – Aug '20)
Startup providing face recognition and liveness detection solutions.
Built masked/peri-ocular face recognition for masked faces and a real-time face liveness SDK (client SDKs for mobile and backend services) used in Aadhaar e-KYC and fraud-prevention flows, handling 100K+ verifications/day.
Platform enabling social commerce through chatbots and automation.
Built NLP-based conversational AI flows for a social commerce chatbot platform by integrating backend APIs and a menu-digitization model for automated restaurant menu parsing, using ML-based intent and NER models.
Financial technology firm providing AI-driven valuation tools.
Developed ML- and rule-based crawlers and pipelines to scrape and structure company information, powering richer company profiles for downstream pipelines.
Startup focused on automated trading solutions for retail investors.
Experimented with genetic programming to explore trading rules and financial technical analysis using Selenium for automation.