Amherst, Massachusetts
Hi there,
I'm Vaishnavi Daber
I am a second year MS CS student at University of Massachusetts, Amherst, and I'm currently working at Big Tomato Tech Co-op as a Software and AI Engineer.
A little about me
I am in my final sem, here at UMass. My academic interests lie in Software Engineering, Distributed Systems, Machine Learning, and quite recently Reinforcement Learning. Prior to my Masters, I worked as a Full Stack Software Developer at LTIMindtree, which originally sparked my interest in large-scale software development. I gain immense satisfaction from creating products and features that help a multitude of users, and I wish to bring my expertise to innovative projects that can make a significant impact.
My ultimate goal is to leverage my holistic expertise in software development and machine learning to develop robust and scalable solutions that address real-world problems and enhance user experiences.
On days when I am not coding, you would find me singing to myself, binge-watching shows or taking a stroll through Amherst at the golden hour.
I have an unwavering passion and energy for people, which has been a huge asset in my career. I believe that building great products comes from genuine empathy, and that happens best through open collaboration—bringing together different perspectives, learning from each other, and working toward a shared vision.
Education
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University of Massachusetts
Current
Master of Science in Computer Science
3.96 CGPA
May, 2025
Relevant Courses: Algorithms, Applied Statistics, Machine Learning, Neural Networks, Data Science, Operating Systems, Intelligent Visual Computing, Reinforcement Learning
University of Mumbai
Bachelor of Engineering in Electronics and Telecommunication
9.62 CGPA
June, 2021
Relevant Courses: Structured Programming Approach, Computer Networks, Big Data, Image Processing and Machine Vision
Achievement: Certificate of Merit for securing Departmental Rank 1 among 200 students.
Experience
Oct 2024 – Present
Big Tomato Tech
Software and AI Engineer Co-op | Python, Flask, RAG, LangChain, OpenAI API, ChromaDB
In my role as an AI Developer, I created an AI-driven chatbot to assist over 200+ NAMI (National Alliance on Mental Illness) sites, using cutting-edge technologies like Retrieval Augmented Generation (RAG), LangChain, OpenAI API, and ChromaDB for Vector Databases.
This chatbot automated the resolution of tech support queries, reducing the manual workload of ticket handling. By processing Freshdesk Articles and historical ticket data, I vectorized the information in ChromaDB and stored chat history in PostgreSQL, allowing the system to provide context-aware solutions.
To further enhance user satisfaction, I am designing a full-stack solution using Flask and PostgreSQL, integrating with PHP and WordPress, which would ultimately reduce query resolution time.
This project demonstrated my passion for solving real-world problems using AI, while also improving efficiency and user experience across the NAMI network.
May 2024 – Aug 2024
Triorama.ai
Full Stack Software and AI Intern | Python, React, MongoDB, Gen AI, Conversational AI, E-commerce
In my role as an AI/ML Software Intern at Triorama.ai, I developed an AI-powered Shopping Assistant search plugin for e-commerce websites, enabling dynamic, conversational interactions and personalized product recommendations.
I designed and implemented a Retrieval-Augmented Generation (RAG) pipeline, and the ChatGPT OpenAI API to enhance the conversational AI by optimizing query analysis and product matching, resulting in a 25% increase in conversion rates. Additionally, I used MongoDB to store chat history in order to provide context aware solutions, and built a responsive Budget-Friendly Recommendation tool using the MERN stack, boosting customer engagement by 30%.
This project showcases my ability to leverage AI and advanced development techniques to enhance user experiences with online shopping and drive measurable business outcomes.
June 2021 – July 2023
LTIMindtree
I joined LTIMindtree as a Graduate Engineer Trainee. After an extensive training in Full Stack Development technologies like Python, Java, SpringBoot, OracleDB, Angular, and JUnit, I joined the Google Cloud Practice Unit.
As part of the Global Agency Team at Google LLC, I orchestrated Operational Excellence to enhance a Media Agency’s Flask application by externalizing the app for public users and unifying data from heterogeneous sources.I optimized user decision-making by integrating Google Ads Recommendation data with Search Console data for 500 workspace accounts using BigQuery, achieving low latency data transfer using Firestore.
Streamlined ETL CI/CD pipelines provided a comprehensive analytics workflow, leading to a 30% surge in search activity and we leveraged Angular for front-end, crafting a responsive UI/UX, and boosting engagement by 20%.
Furthermore, I augmented the login and authentication by transitioning from Okta to Google, revamping scalable RBAC, and automating the onboarding and offboarding of 3000 external users.
Skills
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Java
Python
C
C++
R
HTML5
CSS3
Javascript
SQL
OracleDB
MySQL
Cloud SQL
Big Query
PostgreSQL
MongoDB
Firestore
Javascript
Typescript
Amazon Web Services
Google Cloud Platform
IBM Cloud Platform
Kubernetes
Google Ads API
Google Search Console
Dockers
SpringBoot
Hibernate Java Frameworks
Angular
React
Node.js
Vue.js
JAX
OAuth
Github
Tensorflow
Pandas
PyTorch
Figma
OpenCV
ChromaDB
Flask
RAGs
Langchain
Vector Databases
Contact Me
Drop me a mail if you're looking to hire for a relevant role
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