Hi, I’m Atharva Wandile, a Senior Software Engineer at Aptiv with a Masters in CS from Northeastern University. I specialize in GenAI, RAG systems, and distributed AI applications with over 4 years of experience building efficient ML solutions and data pipelines.

Work Background

I currently work as a Senior Software Engineer at Aptiv, where I develop cutting-edge AI solutions including edge-device communication frameworks using Google’s Agent2Agent protocol and neural network intent classifiers with 90% accuracy. Previously at Oak AI, I spearheaded development of Retrieval Augmented Generation (RAG) frameworks for contextual chatbots and implemented storage optimization algorithms that improved database efficiency by 20%.

My experience also includes roles at Redbus, where I designed big data pipelines that improved customer retention by 10% and slashed processing times by 200% through distributed Spark implementations on AWS. I’m proficient in Python, Java, Go, SQL, and various AI frameworks including LangChain, LangGraph, PyTorch, and TensorFlow.

Technical Focus

I specialize in developing AI systems that solve real business problems, from requirement analysis tools that saved 35% in design review time to test case optimization frameworks using graph databases that saved $100K annually. My expertise spans GenAI applications, RAG systems, multi-agent frameworks, and efficient data pipelines for model evaluation.

Research Interests

My passion lies in reinforcement learning and multi-agent systems. At Northeastern University, I implemented novel continuous macro-action environments for Multi-Agent Reinforcement Learning and achieved state-of-the-art performance using option-critic and actor-critic algorithms. During my undergraduate studies, I conducted research at AllGo Embedded Systems on driver activity detection using computer vision and deep learning, achieving 86% accuracy in real-time classification.

Hobbies

Beyond coding, you’ll find me strumming tunes on my guitar or playing tennis.