About me

TL;DR ➡️ Machine Learning Engineer × Data Scientist × Software Engineer ➡️ 3+ years of experience across Machine Learning, Software Engineering, and Data Science I currently work on enterprise-scale Generative AI systems at ALS, contributing to the development and scaling of a global GenAI platform with multi-agent and multimodal capabilities. My focus includes production architecture, AI governance, and cost-efficient large-scale deployment. At ALS Geoanlytics, I worked in Mineral Exploration and Geoscience, applied Deep Learning and Image Processing to complex geological datasets and translated AI research into operational impact. Previously at Statistics Canada, I developed a Crop Classification and Regression Deep Learning model that accurately predicted crop content and acreage across three Canadian provinces, strengthening my expertise in remote sensing and geospatial analytics. Before my master’s, I worked as a Backend Software Engineer using Spring Boot and AWS, building scalable APIs and distributed systems. I also served as a Deep Learning Research Intern across research groups in India, further shaping my passion for applied AI. Outside work, I actively implement research papers in ML/DL, solve algorithmic problems, and optimize SQL queries on LeetCode. I’m also an avid bird-watcher, hiker, and enjoy cricket, soccer, and tennis. ⸻ Technical Proficiencies • Generative AI (LLMs, Agents, RAG, Multimodal Systems) • Deep Learning (CV/NLP) • Machine Learning • Cloud-Native Architecture & DevOps • AI Governance & Cost Optimization • Remote Sensing & Geospatial Analytics • Data Engineering (Databricks, PySpark) • Backend & API Development ⸻ Technical Skills Languages: Python, R, Java, SQL, MATLAB, C++, JavaScript GenAI & AI: Vercel AI SDK, LLM integrations, multi-agent workflows, RAG pipelines, TTS/STT ML/DL Libraries: PyTorch, TensorFlow, Keras, scikit-learn, Pandas, NumPy, OpenCV, NLTK Data & Big Data: Databricks, PySpark, Hadoop, Kafka, Hive, Tableau Cloud & DevOps: Azure, AWS, Docker, Kubernetes, Kubeflow, CI/CD Databases: MySQL, PostgreSQL, MongoDB, Azure CosmosDB (Mongo API), NeptuneDB SWE Stack: Spring Boot, REST, GraphQL, ReactJS, Next.js, FastAPI, Git, Jira ⸻ 📩 Feel free to connect here or reach out at [email protected] for exciting opportunities.