Open to opportunities

Kunal Bhardwaj

@kunalbhardwaj

Message

Data Scientist building agentic AI and RAG systems that improve real-world outcomes.

Zimbabwe

Message

What I'm looking for

I’m looking to build production AI—agentic systems, RAG, and MLOps—where I can ship end-to-end solutions, collaborate with product and engineering, and drive measurable improvements through experimentation and responsible model deployment.

I’m a Data Scientist and Applied AI Scientist focused on building end-to-end ML systems with transformer models, RAG architectures, and agentic workflows. At HRS GROUP, I architected solutions that delivered a 30% improvement in customer query resolution accuracy, built production data pipelines processing 10M+ daily events with AWS Glue and Apache Airflow, and drove MLOps with CI/CD for model versioning, monitoring, and automated retraining.

I also lead with product impact: I designed predictive dashboards for C-suite decision-making and built an agentic AI platform that turns problem statements into structured project workflows, including Jira-ready task breakdowns. Earlier, as a Technical Product Manager Intern, I developed ML-driven features with projected 2% revenue impact, and I led an AI research team working on computer vision waste classification—grounded in practical deployment and measurable outcomes.

Experience

Work history, roles, and key accomplishments

Current

Data Scientist

Current

HRS Group

Oct 2023 - Present (2 years 9 months)

Architected end-to-end ML solutions using transformer models and RAG, improving customer query resolution accuracy. Built production data pipelines with AWS Glue and Apache Airflow, and led MLOps CI/CD for model versioning, monitoring, and automated retraining.

Transformer Models RAG Agentic AI AWS Glue Apache Airflow Data Pipelines MLOps CI CD Model Versioning Model Monitoring

Technical Product Manager Intern

Apptio

Apr 2023 - Jun 2023 (2 months)

Designed ML-driven product features leveraging customer behavioral data, including segmentation-based approaches for recommendations and anomaly detection. Developed technical specifications and user stories for AI-powered capabilities.

Customer Segmentation Recommendation Systems Anomaly Detection Technical Specifications User Stories

AI Research Team Lead & Incubatee

Atal Incubation Centre

Sep 2021 - Apr 2022 (7 months)

Led a cross-functional team developing a computer vision-based waste classification system using CNN architectures and transfer learning. Served as an AI research team lead and incubatee for the project.

Computer Vision CNN Architectures Transfer Learning Team Leadership