Passionate and driven Senior Machine Learning Engineer with 7+ years of experience applying AI/ML solutions across diverse industries, including finance, legal, life sciences, and ESG. I hold an M.Tech in Computer Science and have a proven track record of transforming complex business problems into scalable, impactful solutions. In my current role, I manage large-scale data processing pipelines handling 8-10 million documents/day, where I’ve custom-trained models and integrated large language models (LLMs) to power a recommendation engine for the ESG domain. My work focuses on productionizing ML models with minimal latency, optimizing robust pipelines for scale, and implementing async and queue processing across both Azure and AWS environments. I’ve also built and optimized vector databases (Qdrant, FAISS) to support high-demand workloads. Key Skills and Interests Core Competencies: Expertise in NLP, Computer Vision, Knowledge Graphs, HPC, and scalable AI/ML solutions. Technical Skills: Proficient in Python, C, Java, and frameworks like TensorFlow, Transformers, Scikit-learn, OpenCV, Numpy, Pandas, Spacy, NLTK, Gensim, FAISS, CUDA, Django, and Celery. Cloud & Database: Azure, AWS, and vector databases, optimized for high-performance applications. I’m continually inspired by fields like Entrepreneurship, Private Equity & VC, and cutting-edge technology in AI. I’m always looking to push boundaries and create meaningful impact through AI-driven innovation.