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Mousumee Acharya

@mousumeeacharya

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AI engineer specializing in production ML and scalable generative AI systems.

India

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What I'm looking for

I seek roles building production-ready ML/Generative AI systems with emphasis on scalable data pipelines, RAG/NER, and measurable business impact in collaborative teams.

I am an AI engineer with deep experience building production-grade ML and generative AI systems, focusing on scalable Python workflows, data ingestion, feature engineering, and deployment. I have delivered cost-efficient solutions across marketing, credit risk, and industrial monitoring, with measurable improvements such as a 40% reduction in prompt token usage and an ROC-AUC of 0.88 for credit-risk models.

I design and implement RAG systems, NER-driven feature extraction, human-in-the-loop feedback loops, and monitoring pipelines using tools like TensorFlow, PyTorch, AWS, Docker, and Flask. I bring an academic foundation (M.Tech) and industry experience across consulting and product teams to build production-ready, maintainable AI infrastructure that drives business impact.

Experience

Work history, roles, and key accomplishments

Current

AI Engineer

Current

WonderLens Labs

May 2025 - Present (10 months)

Built NER-driven feature extraction and production-grade RAG systems for automated marketing asset creation, reducing prompt token usage by 40% and incorporating human-in-the-loop feedback to iteratively improve model performance.

NER RAG Python Data Ingestion Prompt Engineering Human In The Loop Deployment AWS Docker

Teacher (Part-time)

Vibgyor Primary School

Jan 2025 - Nov 2025 (10 months)

Delivered part-time primary school instruction and classroom management, supporting student learning and assessment activities.

Classroom Management Lesson planning Assessments Communication Child Development

Assistant Professor

NIT Kurukshetra

Aug 2018 - Apr 2019 (8 months)

Taught undergraduate courses and guided labs in instrumentation and electronics, contributing to curriculum delivery and student evaluation during academic appointment.

Teaching Curriculum Development Academic Assessment Mentoring Signal Processing Instrumentation

Business Technology Analyst

Deloitte USI

Jan 2013 - Jan 2016 (3 years)

Designed Python and SQL data pipelines and feature engineering frameworks for predictive analytics, contributing to credit risk models with ROC-AUC of 0.88 and a computer-vision preprocessing pipeline achieving 78% accuracy for sludge-settling prediction.

Python SQL Random Forest Logistic Regression Computer Vision Model Evaluation Deployment Monitoring