# Dishank Jhaveri > Software Engineer @ Hippocratic AI Location: San Francisco Bay Area, United States Profile: https://flows.cv/dishank Self Driven Computer Science Engineer with a special interest in Data Science and Machine Learning. Looking to further develop my skill set and knowledge by participating in challenging engineering and technical problems. ## Work Experience ### Software Engineer @ Hippocratic AI Jan 2025 – Present | Palo Alto, CA ### AI Engineer @ Neurality Health Jan 2025 – Jan 2025 | Santa Clara, California, United States • Designed, developed, and shipped production-grade voice AI agents for appointment scheduling, clinical documentation, and insurance verification, deployed on GCP (Cloud Run/GKE) with autoscaling and Cloud Logging/Monitoring, handling 10K+ calls per week. • Researched and iterated on agentic architectures, tool-calling LLM workflows (LangGraph) and deployed production MCP servers for standardized, authenticated, rate-limited tool access. • Built internal AI copilots for customer-support triage, lead generation, and market research, integrating Slack, Calendly and other services to reduce manual workload by 90% ### Machine Learning Intern @ Graphite Jan 2024 – Jan 2024 | Amherst, Massachusetts, United States • Developed a SELF-DISCOVER method for long-form text style transfer, integrating contrastive style guides with LLMs, achieving a 44% improvement in target style accuracy and enabling human-editable guidelines for publication-grade content. • Created a benchmark dataset of 600,000 semantically-paired documents across 5 domains (Tech, Entertainment, Finance, Food, Games), leveraging IoU scoring over Google keyword searches and TF-IDF for precise style differentiation. • Designed and tested zero-shot, few-shot, and SELF-DISCOVER prompting strategies, incorporating BERT embeddings and Longformer models, boosting contextual precision by 30% in AI-driven writing tools. • Trained classifiers on formality, politeness, humor, and simplicity, reducing stylistic deviation by 25% compared to baselines, as validated on a 100-pair benchmark subset. ### Teaching Assistant (CS420 - Software Entrepreneurship) @ University of Massachusetts Amherst Jan 2023 – Jan 2024 | Amherst, Massachusetts, United States • Led software development projects from 0 to 1, driving products from concept to production-ready state and guiding 40+ students through the development process. • Collaborated with Dr. Neena Thota to streamline project mentorship, resolving complex technical challenges in real-time and implementing a rigorous grading rubric that improved student feedback loops by 20%. ### Machine Learning Engineer @ StreetStyleStore Jan 2022 – Jan 2022 | Mumbai, Maharashtra, India • Engineered efficient ETL pipelines: Utilized Apache Kafka and Airbyte to integrate 14 data sources (PostgreSQL, REST APIs, and AWS S3 buckets). This reduced processing latency by 15%, enabling real-time data availability that powered machine learning models like Random Forests and LightGBM for actionable business insights. • Crafted Python-based data parsing tools to transform unstructured datasets, cutting error rates by 28% • Developed a recommendation system using collaborative filtering: Implemented the system with Apache Mahout, analyzing user behavior and purchase history to deliver tailored product suggestions. • Implemented customer segmentation with K-means clustering: Applied scikit-learn to categorize users based on purchasing behavior and preferences, enabling precise targeting for marketing campaigns. ### ML Research Intern @ Vellore Institute of Technology Jan 2021 – Jan 2021 • Engineered a Python-based GUI using Tkinter for real-time SAR image noise reduction, integrating multi-threaded speckle filtering with Gaussian blur and Median Filters • Designed Neuro-Fuzzy Deep Learning models with PyTorch to perform SAR change detection, used grid search and Bayesian optimization to fine-tune model parameters, cutting computational runtime by 25% while preserving high accuracy • Developed a cross-validation pipeline to benchmark noise reduction techniques, ensuring robustness across diverse SAR image datasets. ### Full-stack Developer @ Sigma Tenant Jan 2020 – Jan 2020 | Mumbai, Maharashtra, India • Developed REST APIs using Node.js to facilitate seamless data exchange between the front-end and back-end, contributing to a 30% improvement in development speed. • Implemented CI/CD pipelines using Jenkins, automating the build, test, and deployment processes, which increased development efficiency by 25%. • Optimized code with lazy loading, G-Zip compression, reducing loading times by 70ms. ## Education ### Master of Science - MS in Computer Science University of Massachusetts Amherst ### Bachelor of Technology - BTech in Computer Science Vellore Institute of Technology ## Contact & Social - LinkedIn: https://linkedin.com/in/dishankjhaveri - GitHub: https://github.com/dishank19 --- Source: https://flows.cv/dishank JSON Resume: https://flows.cv/dishank/resume.json Last updated: 2026-04-11