You can read my blog "The Curiosity Ledger"
About Me
Hello! I'm Jenil Shah, an Engineering Manager based in Seattle, Washington. With a passion for technology and innovation, I've worked across various domains with primary focus on recommendation systems, personalization, and AI.
I have my feet firmly planted in two worlds: my heart beats in code as a Software Engineer, and my brain buzzes with strategy as an Engineering Manager. My interests span across productivity, machine learning, LLMs, finance and outdoor activities.
Professional Experience
Books Recommendation Experiences, Amazon
I lead and manage a fantastic team of engineers who build Books Similarities and Personalization experiences for all Amazon Books users. We work on enhancing book recommendations across various platforms like the Amazon website and app, Kindle, and Search. My team is all about innovating the customer experience in recommendations space.
Books Personalization, Amazon
I led a team to craft personalized experiences for book lovers on Amazon. I ideated and built data platforms, both streaming and batch, to support the books ecosystem. I also spearheaded the adoption of orchestration frameworks and led efforts in developing internal data science modelling platform.
Alexa AI, Amazon
As one of the early engineers on Alexa AI, I tackled dynamic ranking and arbitration challenges for Alexa skills. I collaborated closely with scientists to address complex large-scale domain classification issues involving thousands of Alexa skills. You can read more about our work here.
Ford
If you've used a high-end Ford vehicle, you've likely experienced the 360-degree and towing features through the Ford sync panel. Before these features hit production, I simulated them using tools like Qt, Matlab, and Simulink to catch and fix edge cases. This work was done through Tata Consultancy Services.
External Contributions
Open Source AI Hackathon - Hackathon Judge
Served as a judge at the Open Source AI hackathon in Seattle, hosted at Microsoft Reactor. The event, organized by the Open Source AI community led by Yujian Tang, brought together 13+ teams of tech professionals. Engaged with participating teams throughout the day, exploring their project motivations and discussing technological approaches.
IEEE Student Webmaster
Served as the IEEE Student Webmaster, managing and developing web resources for IEEE student members, facilitating communication and resource sharing within the university. Organized and managed national events with 500+ student participation
Journal/Academic Papers
Simple and Effective OCR
Authored a research paper presenting a simple and effective Optical Character Recognition system (OCR) for accurate detection of digits. The system classifies 0-9 digits into four groups using background pixel range and uses intrinsic ratio as mathematical parameter for distinct identification. The paper also addresses overlapping digits recognition using curved contour coordinates. Read the full paper here.
Feature Based Opinion Mining of Amazon and Best Buy Reviews
Dynamic Feature classification and Review categorization of Amazon and Best Buy Reviews. Implemented a complete Data Science Pipeline including Data Cleaning, Data Integration, Prediction, and Visualization. Project featured extensive use of Natural Language Processing and Data Mining techniques. Read the full paper here.
Weekend Projects and Prototypes
ncovindia
Developed a web application tracking COVID-19 statistics in India, providing real-time data visualization and analysis to help users stay informed during the pandemic.