Tarini Mohapatra

Background

About Tarini Mohapatra

Driven and results-oriented AI/Machine Learning Engineer with 4 years of dedicated experience in architecting, building, and deploying robust, production-grade ML systems. My expertise lies in leveraging Python, advanced MLOps methodologies (Docker, CI/CD, Monitoring), and scalable backend technologies (FastAPI, Flask, Redis) to deliver significant performance improvements and innovative AI solutions.Throughout my career, I've successfully:Spearheaded ML initiatives, developing and deploying scalable models and agentic workflows (PyTorch, langGraph, Generative AI) within containerized production environments.Architected and maintained efficient backend microservices (FastAPI) for ML model serving and seamless workflow integration.Implemented and managed CI/CD pipelines (Jenkins), reducing ML model deployment time by 40% and optimizing system monitoring with Prometheus and Grafana.Engineered end-to-end ML pipelines, reducing API response times by 30% and improving collector productivity by 20% through transformer-based intent classification.Leveraged Generative AI and LLMs to achieve an 87% performance in deriving actionable insights from call summaries, a 20% leap over previous solutions.Driven substantial efficiency gains, such as an 80% reduction in key process latency through Redis caching and Python multiprocessing during my internship.I am proficient in a comprehensive suite of tools and technologies, including PyTorch, Hugging Face, NLP, LLMs, FastAPI, Flask, Docker, Jenkins, MLFlow, AWS, and GCP. I am passionate about tackling complex challenges and building reliable, cutting-edge AI solutions.