Baladithya Balamurugan

I'm a Solutions Architect at Baseten, working with customers on model deployment and inference performance. My focus is AI infrastructure and the engineering behind fast, reliable, cost-effective inference, including model serving, GPU workloads, runtimes, routing, and scaling. I enjoy working directly with engineering teams to understand their bottlenecks, build solutions, and bring that feedback into product development.

Before Baseten, I spent four years at AWS designing and implementing cloud solutions, drawing on machine learning, algorithm analysis, and Python programming. My work focused on generative AI, including Amazon Bedrock, fine-tuning and agentic architectures, NVIDIA Dynamo on Amazon EKS, LoRAX multi-tenant serving, and voice authentication research. I also helped customers with cloud architecture, capacity planning, and deployment, and shared technical guidance through published articles, hackathons, and university sessions.

Earlier, I worked as a Software Developer at the UC Santa Cruz Genomics Institute and a Research Intern at the Johns Hopkins Applied Physics Laboratory. My work covered data migration, reindexing, Git-based development, user interfaces, simulation environments, and brain-computer interfaces. Those roles built my experience in cloud technologies, data engineering, and AI, and in collaborating across research and engineering teams.

I completed my M.S. in Computer Science at the University of Southern California in May 2024 while working full-time at AWS, building on my interests in machine learning, cloud computing, and software engineering. I earned my B.S. in Computer Science at UC Santa Cruz in March 2022, graduating with honors, and have completed training and certifications from Google and AWS. I enjoy learning new technologies and applying them to real-world problems.