AI/ML engineer Artifical intelligence machine learning data engineer
Resume:
Praneeth Rikka
469-***-**** ****************@*****.***
PROFESSIONAL SUMMARY
Aspiring AI/ML Engineer with hands-on experience in developing machine learning models, AI solutions, and data pipelines. Proficient in leveraging cutting-edge technologies like TensorFlow, PyTorch, and NLP techniques to build scalable AI applications. Strong expertise in data preprocessing, model fine-tuning, and deployment of AI solutions in cloud environments. Passionate about applying AI to solve real-world business problems and drive innovation.
SKILLS
- Programming Languages: Python, SQL, R
- Machine Learning: Supervised & Unsupervised Learning, Neural Networks, NLP, Computer Vision, LLM Fine-Tuning, Retrieval-Augmented Generation
- AI Frameworks: TensorFlow, PyTorch, Scikit-learn, Hugging Face Transformers
- Data Engineering: ETL Pipelines, API Integration, Web Scraping, PostgreSQL, AWS
- Cloud Technologies: AWS (S3, Lambda, EC2, SageMaker)
- Data Visualization: Tableau, Power BI, Matplotlib, Seaborn
- DevOps & MLOps: Docker, GitHub Actions, Airflow
EXPERIENCE
University of North Texas, Denton, TX
Research Data Scientist
January 2023 – September 2024
- Built and deployed LLM-powered metadata extraction models using TensorFlow and PyTorch, enhancing document classification accuracy by 20%.
- Automated data pipelines for web scraping and API data ingestion using Selenium and BeautifulSoup, reducing manual intervention by 50%.
- Developed and fine-tuned large language models (Llama, Gemini) to improve text classification workflows.
- Created scalable REST APIs to facilitate metadata retrieval and integration with downstream applications.
- Conducted model performance evaluation and hyperparameter tuning using GridSearchCV and Optuna.
University of North Texas, Denton, TX
Graduate Research Assistant – Data Science
October 2022 – December 2022
- Engineered SQL-based data warehouses, reducing query execution time by 30%.
- Implemented NLP-based document classification pipelines to improve metadata accuracy.
- Automated periodic data ingestion tasks using Airflow to improve pipeline efficiency.
- Performed data wrangling, cleaning, and feature engineering to optimize model performance.
IIIT - Indicwiki, Hyderabad, India
Data Scientist
June 2021 – January 2022
- Built machine learning models for multilingual text classification, achieving a 50% improvement in data ingestion efficiency.
- Developed custom tokenization pipelines for rare Indian languages.
- Exposed text classification models via Flask-based APIs.
SmartInternz, Hyderabad, India
Data Scientist Intern
January 2020 – January 2021
- Developed a predictive analytics model for life expectancy estimation with 97% accuracy.
- Deployed predictive models to cloud environments using AWS Lambda.
- Presented insights to stakeholders through interactive dashboards.
PROJECTS
- Article Classification Using OCR and BERT: Designed OCR pipelines integrated with BERT models to improve metadata classification accuracy by 30%. Developed ETL pipelines, fine-tuned models, and automated deployment using Docker and Flask.
- Spoken Language Identification: Developed CNN-based language classification models with 94% accuracy. Designed data augmentation pipelines, tuned hyperparameters, and automated deployment with TensorFlow Serving.
- Generative AI Chatbot: Built a custom chatbot using GPT models. Integrated APIs, implemented prompt engineering, and deployed with AWS Lambda and API Gateway.
CERTIFICATIONS
- AWS Certified Machine Learning – Specialty
- TensorFlow Developer Certificate
- IBM Data Science Professional Certificate
EDUCATION
Master of Science in Data Science
University of North Texas, May 2024
GPA: 3.82 / 4.0
PUBLICATIONS
- "Can LLMs Categorize Specialized Documents from Web Archives Better?" – Joint Conference on Digital Libraries (JCDL)
- "Investigations Using Machine Learning Models to Automate Sorting of Texas Digital Publications" – Texas Conference on Digital Libraries
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