machine learning engineer

Prashanth Bandari

*********.*********@*****.*** LinkedIn +1-480-***-****

Education

Northern Arizona University Aug 2023 -Dec 2024

Master of Science, Information Technology

Experience

Machine Learning Engineer Intern Think Book Feb 2023 - Aug 2023

• Built and deployed scalable recommendation systems, improving personalization accuracy by 30%.

• Conducted exploratory data analysis to derive insights and enhance model performance by 25%.

• Deployed ML pipelines on AWS using SageMaker, Lambda, EC2, and S3, improving efficiency by 35%.

• Managed and queried large datasets using SQL and PostgreSQL, reducing processing time by 40%.

• Applied MLOps best practices: CI/CD, model versioning, automated retraining, and model monitoring.

• Fine-tuned transformer-based language models and developed LLM pipelines for specific domains.

• Participated in LLM evaluation, benchmarking model performance on downstream recommendation tasks.

Data Scientist Intern ProtoHubs.io May 2022 - Jul 2022

• Designed a real-time course recommendation engine using Python, Pandas, and TensorFlow.

• Applied A/B testing to refine recommendation strategies, improving engagement rates.

• Deployed models using AWS EC2 and Lambda to ensure responsiveness and scalability.

• Automated model feedback loop for periodic retraining aligned with user behavior. Projects

VR-Based Intelligent Course Recommendation System Nov 2023 - Dec 2024

• Developed a VR-based recommender system using LSTM and Transformers to personalize children's learning paths.

• Integrated real-time sensor feedback to adapt recommendations and enhance user engagement. AI Chatbot for Customer Support with Sentiment Analysis Apr 2023 - May 2024

• Created an AI-powered chatbot using Rasa and Hugging Face Transformers for customer queries. Integrated sentiment analysis using VADER & BERT.

• Deployed chatbot on web platforms and built a real-time analytics dashboard for monitoring sentiment and chatbot performance.

Certifications

• AWS Certified Machine Learning Engineer – Associate

• Academy Accreditation: Generative AI Fundamentals – Databricks Skills

• Machine Learning & AI: Recommendation Systems, Fraud Detection, AI Chatbots, Sentiment Analysis (BERT, VADER), Deep Learning (TensorFlow, PyTorch, CNN, RNN, LSTMs, Transformers, Autoencoders), Model Optimization, MLOps (CI/CD for ML, Model Monitoring, Model Versioning, Automated Pipelines)

• Big Data & Streaming: Apache Kafka, Spark Streaming, Large-Scale Data Processing, Real-Time Data Pipelines.

• Cloud & Deployment: AWS (SageMaker, Lambda, EC2, S3), Kubernetes, Docker, Scalable Model Deployment & Optimization, CI/CD for ML.

• Programming & Databases: Python (Pandas, NumPy, TensorFlow), SQL, PostgreSQL, A/B Testing.

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