Professional Overview
I am a dedicated and experienced Software Engineer with a robust background in AI accelerators, machine learning, and data science. My professional journey spans over two years at Multicoreware, Chennai, where I have honed my skills in kernel development for ONNX and Pytorch operations, optimizing kernels for maximum hardware utilization, and providing support for complex AI systems. I have a proven track record of delivering high-quality solutions that meet and exceed customer expectations.In addition to my engineering role, I have hands-on experience in academia as an Assistant Professor of Artificial Intelligence and Data Science, where I developed and delivered curriculum that catered to the needs of aspiring data scientists. My internship as a Data Science Intern at Exposys Data Labs further solidified my expertise in handling real-world data science projects.Throughout my career, I have been the primary point of contact for customer-facing activities, leading weekly update calls and ensuring clear and transparent communication. This has enabled me to build strong relationships with clients, ensuring their satisfaction and the successful delivery of projects.My educational background includes an M.Tech from SSN College of Engineering and a B.Tech from Perunthalaivar Kamarajar Institute of Engineering and Technology, both with excellent academic records. I am proficient in multiple programming languages, including C++, Python, and have a solid understanding of using Kubernetes for scalable and efficient project deployment.I am passionate about leveraging my skills to solve complex problems and deliver impactful solutions. My areas of interest include machine learning, deep learning, data science, computer vision, and blockchain technology. I continuously strive to learn and adapt to new challenges, aiming to provide the best possible outcomes for my clients.
Areas of Expertise
NLP & Prompt Engineering
Build natural language processing systems, fine-tune large language models, and craft reliable production prompts for AI-powered products.
AI & Machine Learning Engineers
Design, train, and ship production ML models — from data pipelines to model inference at scale. Covers supervised learning, neural networks, LLM integration, and model optimisation.
Data Science & Analytics
Extract business insights from raw data using statistical modelling, predictive analytics, A/B testing, and interactive dashboards.
MLOps & AI Infrastructure
Architect scalable ML infrastructure — CI/CD for ML, model versioning, experiment tracking, monitoring, and cloud deployment on AWS, GCP, or Azure.
