Hi, I'm Harika, an AI/ML engineer with 5+ years of hands-on experience building and deploying machine learning, deep learning, and GenAI solutions. I enjoy turning complex data into actionable insights and scalable products, and I thrive in fast-paced environments where collaboration across teams drives impact. My go-to toolkit includes Python, TensorFlow, PyTorch, and Scikit-learn, with applied work in NLP, computer vision, and predictive analytics. I have designed and deployed LLM-based systems using LangChain, LangGraph, and RAG pipelines with vector databases like Pinecone, FAISS, Weaviate, and Milvus. I focus on robust MLOps—containerized deployments, CI/CD, and model versioning—to ensure reliable, production-ready AI solutions. I’m excited to continue delivering practical, high-impact AI across finance and beyond.

Harika P

Hi, I'm Harika, an AI/ML engineer with 5+ years of hands-on experience building and deploying machine learning, deep learning, and GenAI solutions. I enjoy turning complex data into actionable insights and scalable products, and I thrive in fast-paced environments where collaboration across teams drives impact. My go-to toolkit includes Python, TensorFlow, PyTorch, and Scikit-learn, with applied work in NLP, computer vision, and predictive analytics. I have designed and deployed LLM-based systems using LangChain, LangGraph, and RAG pipelines with vector databases like Pinecone, FAISS, Weaviate, and Milvus. I focus on robust MLOps—containerized deployments, CI/CD, and model versioning—to ensure reliable, production-ready AI solutions. I’m excited to continue delivering practical, high-impact AI across finance and beyond.

Available to hire

Hi, I’m Harika, an AI/ML engineer with 5+ years of hands-on experience building and deploying machine learning, deep learning, and GenAI solutions. I enjoy turning complex data into actionable insights and scalable products, and I thrive in fast-paced environments where collaboration across teams drives impact. My go-to toolkit includes Python, TensorFlow, PyTorch, and Scikit-learn, with applied work in NLP, computer vision, and predictive analytics.

I have designed and deployed LLM-based systems using LangChain, LangGraph, and RAG pipelines with vector databases like Pinecone, FAISS, Weaviate, and Milvus. I focus on robust MLOps—containerized deployments, CI/CD, and model versioning—to ensure reliable, production-ready AI solutions. I’m excited to continue delivering practical, high-impact AI across finance and beyond.

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Experience Level

Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Intermediate
Intermediate
Intermediate
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Language

English
Fluent

Work Experience

Machine Learning Engineer at Zensar Technologies
August 1, 2019 - July 31, 2023
Designed and trained supervised models (Decision Trees, Random Forest, Naive Bayes, XGBoost) to predict customer churn and loan default risk with 89% accuracy, reducing manual review duration by 35%. Developed deep learning architectures (RNNs, CNNs) in Keras and PyTorch for sentiment and image classification, improving F1-score by 22% over baselines. Implemented unsupervised algorithms (K-Means, DBSCAN, PCA) for transaction data segmentation and anomaly detection, identifying fraud clusters previously missed by rule-based systems by 60%. Optimized NLP workflows using BERT, NLTK, and SpaCy for entity recognition and intent analysis, enhancing text classification precision by 30%. Delivered interactive dashboards via Power BI integrated with Azure ML APIs to monitor model drift across production environments by 35%.

Education

Master of Science in Artificial Intelligence at The University of North Texas
January 11, 2030 - May 1, 2025

Qualifications

AWS Machine Learning Associate
January 11, 2030 - June 29, 2026
AWS Certified Data Engineer
January 11, 2030 - June 29, 2026
Azure AI Fundamentals
January 11, 2030 - June 29, 2026

Industry Experience

Financial Services, Software & Internet, Professional Services