Hi, I’m Deepak Kumar, an AI/ML engineer with around four years of hands-on experience designing and deploying scalable machine learning systems. I’ve built end-to-end ML pipelines, advanced generative AI capabilities, and data engineering solutions across cybersecurity, healthcare, and enterprise environments. I enjoy turning complex technical problems into measurable business impact and collaborating with cross-functional teams to drive real-world outcomes.
I specialize in end-to-end ML pipelines using Python, TensorFlow, XGBoost, and Spark, with hands-on expertise in unsupervised anomaly detection, time-series forecasting, and model explainability. I’ve worked on RAG-based systems, fine-tuning LLMs with LoRA, and integrating vector databases. I’ve deployed low-latency inference services on Kubernetes and cloud platforms, and I’m proficient in monitoring, drift detection, and production-grade ML ops practices. I’m passionate about translating technical challenges into tangible improvements in operational efficiency and decision-making through AI-driven solutions.
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