Sudipta Pathak, PhD | ML Systems & Infrastructure Engineer

Sudipta Pathak, PhD | ML Systems & Infrastructure Engineer ML Systems & Infrastructure Sudipta Pathak, PhD Open to Principal/Staff RolesUS Citizen - No Sponsorship Required Building scalable ML platforms, distributed training systems, and AI infrastructure. Expert in MLOps, model optimization, and production-grade machine learning. View Resume Download PDF View My Work Scroll to explore About Me I am a Machine Learning Systems Engineer with deep expertise in building production-grade AI infrastructure. My work spans from distributed training systems to edge deployment, with a focus on scalability, efficiency, and reliability. Distributed Training Large-scale model training across GPU clusters with optimized data parallelism and model parallelism strategies. ML Infrastructure Building robust ML platforms with Kubernetes, Kubeflow, and custom orchestration for production workloads. Data Pipelines High-throughput data processing pipelines with Apache Spark, Ray, and modern data lake architectures. Cloud-Native ML Multi-cloud deployments on AWS, GCP, and Azure with focus on cost optimization and scalability. Model Optimization Quantization, pruning, and distillation techniques for deploying efficient models at the edge and cloud. MLOps & Security End-to-end ML lifecycle management with CI/CD, monitoring, and enterprise-grade security practices. Writings Technical blog posts, paper reviews, and tutorials on ML systems, infrastructure, and distributed computing. AI-Assisted Coding Feb 2026•11 min read The Claude Code Field Manual: 13 Battle-Tested Workflows From the Tool's Creator Most developers use Claude Code at 20% of its potential. These 13 workflows -- from parallel instances to feedback loops -- will change how you ship. Fork the repo, work through the exercises, and build muscle memory by end of day. Text-to-SQL Feb 2026•26 min read NL2SQL Benchmark: Vanna AI vs WrenAI vs DB-GPT — 50 Queries, One