Soumya Mukherjee is a technology architect focused on building intelligent, autonomous, and production-grade systems at the intersection of machine learning, agentic AI, and modern software engineering. His work spans applied AI, deep learning, MLOps, intelligent automation, and robotic process automation (RPA), driving scalable solutions across enterprise and cloud environments.

He specializes in end-to-end ML system design—covering data engineering, model development, evaluation, deployment, and monitoring—leveraging frameworks such as PyTorch, TensorFlow, JAX, LangChain, Hugging Face, OpenAI APIs, MLflow, and Ray. His systems integrate with Kubernetes, Terraform, Kafka, and containerized microservices to deliver high-performance, fault-tolerant AI pipelines.

Soumya combines strong software engineering fundamentals with expertise in automation, test orchestration, DevOps, and CI/CD. He has delivered solutions across domains including recommendation systems, time-series forecasting, NLP, computer vision, and agent-based LLM orchestration.

His core interests lie in explainable AI (XAI), agentic workflows, foundation models, RAG pipelines, reinforcement learning, secure infrastructure, and human-AI co-pilots that blend intelligence, autonomy, and trust.