Hello! What would you like to know about Eshan?
You can ask about his work experience, projects, research, or ML skills.
Hi, I am Eshan Chawla
Machine Learning Engineer with background in AI/ML, data engineering, and data-driven product development.
Currently advancing expertise in applied ML through Master’s in Artificial Intelligence at San Jose State University.
Ask Eshan anythingRAG
Ask about experience, skills & projects
AI Assistant
ML Network Intrusion Detection System
A machine learning based system to detect network intrusions with high accuracy.
PythonScikit-LearnMachine LearningSecurity
RAG Based Interactive Resume
Implemented a production-grade RAG deployment on a user-facing portfolio site.
PythonTypescriptNextJSVercelPineconeVertex AI
Re-ranking and Late Interaction Drive Retrieval Quality: A Controlled Comparison of RAG Strategies for Scientific Question Answering
Information RetrievalA controlled comparison of six retrieval-augmented generation (RAG) strategies for scientific question answering, presented at the AIxSET Conference 2026.
RAGInformation RetrievalLLMsColBERTv2Agentic AI
Evaluating MU methods for Image Generation
Diffusion ModelsImplementing and Improving MU methods in Diffusion Models.
Machine UnlearningDiffusion ModelsAI SafetyPrivacyDeep Learning
Work Experience
PocketPills
CA, US
Machine Learning Engineer
Aug 2026 – Dec 2026
- Joining back as an MLE for Fall 2026 to lead AI initiatives for healthcare-specific business process automation.
Apple
New York, NY
Machine Learning Intern
May 2026 – Aug 2026
- Worked in the ML Team for Apple Wallet to contribute to internal platforms for evaluating multi-turn agentic conversations, synthetic dataset generation pipeline, implementing fair LLM-as-a-Judge framework and evaluators for internal coding agent harnesses based on broad literature reviews.
- Audited and worked on policy enforcement and all integration scopes from the wallet team to experiment with payment based capabilities in Agents.
PocketPills
Gurugram, India
Machine Learning Engineer II
Jul 2024 – Jul 2025
- Cut Docker image size by 42% and build time by 30% for the AI service by refactoring vector-embedding workflows to use AWS Bedrock Knowledge Bases instead of a ChromaDB setup.
- Led and mentored a small AI team delivering RAG-based SMS reply agents, call-summarization pipelines, and OCR digitization workflows, collectively saving ~20 hours/week for operations and an estimated $2,000/month.
- Owned integration with Braze and built multi-channel engagement journeys (SMS, email, push) for user re-targeting, using A/B tests and heatmap analysis with marketing to lift customer engagement.
- Reduced Braze data-point consumption by 87% through an optimized, fault-tolerant, API-based data ingestion pipeline, significantly cutting recurring platform costs.
- Improved gross margins by automating web scraping of Canadian drug-outage sources to inform inventory decisions and prioritize stocking of high-demand medications.
Associate Data Analyst
Jul 2023 – Jun 2024
- Worked directly with the CTO, COO, and President to build datasets and financial models used in monthly revenue reviews, shareholder updates, and fundraising decks.
- Decreased working capital by $300k (~1.5 days of revenue) by implementing ML-based time-series forecasting for drug usage, enabling a just-in-time inventory strategy.
- Reduced inbound customer messages by deploying an inbound SMS classification system using clustered BART embeddings, enabling product and UX changes based on message categories.
- Built cost-efficient analytics pipelines using AWS CDC to replicate production DBs into Databricks and integrate incremental data from Mixpanel, Firebase, Google Ads, Typeform, and PostgreSQL.
Data Analyst Intern
Jan 2023 – Jun 2023
- Automated reporting with Google Apps Script to sync Redash data into Google Sheets and send real-time KPI alerts to leadership via Slack, eliminating manual reporting.
- Drove cost reductions by analyzing prescription and order-processing workflows and partnering with Tech and Operations leadership on A/B tests and process optimizations.
- Built Tableau dashboards to monitor team efficiency and call wait times, supporting data-driven staffing and operations decisions.
Saint Louis University
Data Visualization Intern · Mar 2022 – Apr 2022
- Analyzed and optimized campaign performance for global marketing initiatives, highlighting underperforming regions and channels.
- Led a distributed team across time zones to deliver timely reporting, improving clarity and consistency for stakeholders.
Education
San Jose State University
Masters in Artificial Intelligence
Vellore Institute of Technology
Bachelor of Technology in Computer Science
Jul 2019 – Jun 2023
GPA: 3.89/4
Contact
Email: [email protected]
LinkedIn: eshan-chawla
Instagram: chawla.eshan