Summary
Saksham Jindal is a Machine Learning Engineer II with nine years of experience building and productionizing deep learning systems at the intersection of robotics, computer vision, and applied ML for companies like Fractal, TomTom, Metropolis, and Pinterest. He designs modular, reproducible training and inference pipelines (PyTorch/TensorFlow) and has hands-on expertise with distributed training, GPU cluster management, and cloud deployments on GCP. His work spans semantic segmentation, detection, instance segmentation, 3D reconstruction and SE(3)-equivariant representations for deformable-object manipulation, with applied projects in aerial perception and ADAS map generation. Saksham pairs research-driven approaches from his MS in Robotics at UC San Diego with product-minded delivery—exposing models as REST APIs and implementing monitoring and orchestration for real-world use. Active in open source, he’s published practical CV projects (lane detection, face one-shot verification) and maintains a portfolio at saksham.live and GitHub that reflect both research depth and production sensibilities.
9 years of coding experience
3 years of employment as a software developer
University of California, San Diego
Master of Technology - MTech Ocean Engineering and Naval Architecture, Master of Technology - MTech Ocean Engineering and Naval Architecture at Indian Institute of Technology, Kharagpur
High school, High school at Cambridge School Srinivaspuri
Hindi, English