Aditya Choudhary

AI Researcher

San Francisco, California, United States8 yrs 6 mos experience

AI EnabledAI ML Practitioner

Key Highlights

7+ years in Applied Machine Learning and Data Science.
Top 1.5% on Kaggle Competitions among 140,000 participants.
Expertise in Generative AI and Large Language Models.

Stackforce AI infers this person is a SaaS expert specializing in AI-driven solutions for E-commerce.

Contact

aditya.ch512@gmail.com LinkedIn

Skills

Core Skills

Machine LearningAiGenerative AiNlp

Other Skills

Multimodal AIAI AgentsLLM Fine-tuningLarge Language Models (LLM)Conversation AILangChainDeep LearningNeural NetworksApache SparkApache AirflowCloud ComputingAlgorithmsAndroid DevelopmentData StructuresShell Scripting

About

• https://topmate.io/aditya_choudhary5 • 7+ years experience in Applied Machine Learning, Data Science and Backend engineering. • Experienced in GenAI, LLMs, NLP, Deep Learning, conventional ML • Master's in Computer Science from Stony Brook University, NY focused in machine learning, natural language processing and distributed systems. • Currently ranked Top 1.5% out of 140,000 on Kaggle Competitions.

Experience

8 yrs 6 mos

Total Experience

1 yr 10 mos

Average Tenure

11 mos

Current Experience

Palo alto networks

Principal Machine Learning Engineer

Jul 2025 – Present · 11 mos · San Francisco Bay Area

Multimodal AIAI AgentsLLM Fine-tuningMachine LearningAI

Walmart global tech

Senior Data Scientist

Dec 2022 – Jul 2025 · 2 yrs 7 mos · San Francisco Bay Area

Development and deployment of a multi-agent conversational AI system powering intelligent product discovery and shopping experience on Walmart’s mobile app, impacting over 10M+ users.
https://corporate.walmart.com/news/2025/06/06/walmart-the-future-of-shopping-is-agentic-meet-sparky
Architected and developed a modular multi-agent LLM system with components for context aware Q&A generation, Next Query Recommendations, and LLM-as-a-judge evaluation - resulting in 300% increase in user engagement. Led cross-functional collaboration with product, engineering, and UX teams to ensure seamless integration and optimal user experience.
Fine-tuned and deployed Llama-3 based agent that provides multi-turn chat conversation within a dynamic carousel interface, improving user engagement by 30%. (Research paper under review).
Prompt-tuned several LLM-as-a-judge agents to guardrail conversational AI responses for contextual grounding, blocking any harmful content and adhering to company guidelines.
Developed a clustering-based unsupervised topic extraction system for the delivery drivers’ chatbot, boosting automation rates from 15% to 74% .

Large Language Models (LLM)Generative AIConversation AIAI AgentsLangChainDeep Learning+3

Vmware

2 roles

Machine Learning Engineer

Feb 2021 – Dec 2022 · 1 yr 10 mos · Palo Alto, California, United States

Developing Unsupervised Anomaly Detection models and their end-to-end production deployment for Endpoint Detection and Response (EDR) system in Carbon Black Security suite.
Autoencoder, Isolation Forest, Approximate Nearest Neighbor Search, TensorFlow, Apache Spark, Airflow, AWS (SageMaker, Glue, Athena, S3), Docker

Software Engineer Intern

Jun 2020 – Aug 2020 · 2 mos · Palo Alto, California, United States

Reduced the mean problem resolution time by 15% by developing native integration of vRLI Cloud system logs for NSX-T components in vRealize Operations SaaS platform.
Technologies used : Java, Spring Boot, AWS EC2

Stony brook university

2 roles

Graduate Research Assistant

Feb 2020 – May 2020 · 3 mos

Working at BrookHaven National Laboratory under the guidance of Dr. Yuewei Lin and Prof. Barbara Chapman.

Graduate Teaching Assistant

Jan 2020 – May 2020 · 4 mos

Graduate teaching assistant for Python programming course.
Responsible for grading assignments and midterms, holding office hours to clear the doubts of undergrad students.

The d. e. shaw group

2 roles

Senior Software Engineer | Machine Learning

Jul 2018 – Jun 2019 · 11 mos · Hyderabad, Telangana, India

Developed NLP based Recommendation system and multi-class Classification applications.
Technologies used: Pytorch, XGBoost, AWS SageMaker, MSSQL, Spring, Git, Docker, Datadog, Elasticsearch

Software Engineer

Jul 2016 – Jun 2018 · 1 yr 11 mos · Hyderabad, Telangana, India

Malaviya national institute of technology jaipur

Summer Research Intern

May 2015 – Jul 2015 · 2 mos

Community Question-Answering Recommendation System: Created a recommendation model which predicts expert users who are most likely to give helpful answers for a newly added question on StackExchange. Publication - https://ieeexplore.ieee.org/document/8710394
Developed hybrid,content-based filtering and graph-based models.
Implemented tf-idf based content-model in Spark distributed model. Setup 15-node Spark cluster in department lab.
Technologies: Spark, Python, Google Compute Engine, TitanDB, Cassandra