Okula Yenugu

Seasoned AI/ML Engineer with 8+ years of experience delivering machine learning solutions that address complex business and operational challenges across multiple industries. Experienced in designing LLM evaluation pipelines, including prompt evaluation, regression testing, and structured scoring methods to ensure consistent model quality across releases. Demonstrated expertise in designing deep learning models using CNNs, RNNs, Transformers, and reinforcement learning for NLP, computer vision, and time-series use cases. Familiar with RLHF concepts and human-in-the-loop feedback systems, applying evaluation techniques such as pairwise comparison and quality benchmarking to improve generative AI outputs. Experienced in building end-to-end data pipelines with Apache Spark, Hadoop, and Snowflake to support large-scale analytics and feature processing. Skilled in developing real-time APIs and services to integrate machine learning models into enterprise platforms and operational systems. Proficient in deploying scalable AI systems on AWS and Azure, using Docker and Kubernetes to support reliable, production-grade workflows. Specialized in natural language processing tasks, including text normalization, NER, intent detection, sentiment analysis, and transformer-based language models such as BERT and GPT-4. Knowledgeable in applying explainability techniques and bias control methods to improve model transparency, trust, and regulatory alignment. Analytical problem-solver with a strong ability to translate business requirements into effective, data-driven AI solutions. Collaborative contributor within Agile teams, using Git, JIRA, and structured delivery practices to support iterative development and on-time releases. Excellent communication and interpersonal skills, adept at explaining complex technical concepts to diverse audiences.