Sri Akash Kadali

About Sri Akash Kadali

I’m Sri Akash Kadali, a master’s student in Applied Machine Learning at the University of Maryland, College Park, with a strong foundation in machine learning, deep learning, computer vision, NLP, generative AI, & medical image analysis. With four research and industry internships across IIT Indore, MNIT Jaipur, Ayar Labs. I’ve built AI systems that span inspection automation, diagnostic imaging, document understanding, and LLM integration. At Ayar Labs, I engineered AI-powered visual inspection systems for silicon photonics and semiconductor dies. My work involved image classification using Vision Transformers, OCR for alphanumeric code recognition, and defect annotation, all optimized for production & embedded into the photonics inspection workflow. These tools accelerated chip validation & significantly reduced human inspection time. In the medical domain, I’ve worked on deep learning pipelines for classification and segmentation of diagnostic image data. These projects emphasized model interpretability, class imbalance handling, and real-world deployment readiness. I applied Grad-CAM and SHAP to ensure transparency in model decisions, critical in healthcare AI. In NLP and generative AI, I’ve fine-tuned Transformer and LoRA-based models for summarization, sentiment analysis, and document understanding using Hugging Face, FastAPI, and Docker. I deployed scalable APIs and interactive web apps backed by Pegasus, T5, and GPT-style models. My projects explored zero-shot and few-shot learning with prompt engineering to adapt LLMs for domain-specific tasks. My experience also covers classical ML for structured data, building gradient boosting and ensemble models with robust feature pipelines. I’ve implemented anomaly detection systems, conducted hyperparameter tuning using Optuna, and trained models for predictive analytics and trend forecasting in time series data. To ensure end-to-end ML maturity, I’ve worked with tools like MLflow, Weights & Biases, Docker, and REST APIs for experiment tracking, containerization, and production inference. I’ve also explored decision systems for constrained optimization tasks & experimented with multi-modal setups where text and image features are combined for joint inference. Currently, I’m seeking full-time roles in ML engineering, computer vision, NLP, LLMs, or generative AI, where I can apply this diverse experience to solve real-world problems with scalable, intelligent systems. If you’re working on bleeding-edge AI, whether in healthcare, hardware, or digital platforms. I’d love to connect and collaborate.

Experience

1. Machine Learning Engineer

   Ayar Labs

   May 2025 — Present · San Jose, CA, US

Education

• Indian Institute of Information Technology Vadodara

  Bachelor of Technology - BTech

  2020 — 2024

• University of Maryland

  Master of Science - MS

  2024 — 2026

• Ravindra Bharathi Global School - India

  SSC

• Sri Gayatri Junior College

  Intermediate Education