Neeta Kannu

WORK HISTORY

EDUCATION

ABOUT NEETA KANNU

I’m an AI Engineer-in-transition with over 8 years of software engineering experience and a recent Master’s degree focused on artificial intelligence, machine learning, and deep learning for real-world and research-driven applications. My journey began in software engineering at global firms like Capgemini, Accolite Digital, and TCS, where I designed scalable APIs, automated infrastructure, and deployed containerized systems using Python, Java.NET, Docker, and Kubernetes. Driven by a passion for intelligent systems, I pursued graduate studies and contributed to impactful AI/ML projects across bioinformatics, NLP, and healthcare analytics. As a Research Assistant at UCCS, I worked on genomic data analysis using GPU-accelerated ML workflows, integrated legacy systems into modern pipelines, and applied statistical techniques to visualize complex Hi-C datasets. My AI work includes 3D chromosome reconstruction via reinforcement learning, heart disease prediction with ensemble models, and accent classification using deep learning on MFCC features. I bring a unique ability to bridge AI research, software engineering, and production deployment—building intelligent systems that are both scientifically sound and operationally scalable. I’m currently seeking roles as an AI Engineer, ML Engineer, or Applied Scientist, where I can apply this blend of experience to solve meaningful, real-world challenges. Key Skills Languages & Frameworks: Python, PyTorch, TensorFlow, Scikit-learn, Keras, Hugging Face Transformers DevOps & Tools: Docker, Kubernetes, Jenkins, Git, Linux AI/ML Domains: Machine Learning, Deep Learning, Artificial Intelligence, NLP, Reinforcement Learning, CNNs, LSTMs Databases: SQL, PostgreSQL, MySQL, Oracle Libraries & Utilities: Pandas, NumPy, Librosa, OpenCV, Matplotlib, PowerShell, Bash