Summary
Atul Dhingra is a Machine Learning Engineer with 10 years of experience building and scaling applied AI across edge perception, autonomous systems, and generative models from the Bay Area. He has led production deployments at scale—from improving edge inference 5× and rolling autonomous checkout to 40+ stores to training multi-billion-parameter agentic LLMs with distributed FSDP on H100/B200 clusters. At PayPal he bridged R&D and production for agentic AI and developer-facing LLMs, improving ML developer productivity by 30%, and at Standard AI he delivered $1M+ annual savings through automation and hardware-aware model engineering. As a founding ML engineer at Dxtr he translated monocular video into synchronized 3D kinematics for robot policy training, reflecting a rare blend of vision, robotics, and systems know-how. Now working on Photos Intelligence at Apple, he pairs research-grade modeling with pragmatic deployment, focusing on latency, quantization, and SLA constraints. Colleagues rely on him for end-to-end ML architecture, fast iteration on edge-constrained models, and mentoring cross-functional teams.
10 years of coding experience
11 years of employment as a software developer
The Army Public School, Dhaula Kuan, New Delhi
Visiting Researcher Computer Vision, Visiting Researcher Computer Vision at International Institute of Information Technology Hyderabad (IIITH)
Master's degree Computer Science, Master's degree Computer Science at Rutgers University
Bachelor of Engineering - BE Instrumentation and Control, Bachelor of Engineering - BE Instrumentation and Control at Netaji Subhas Institute of Technology
Indian Institute of Technology Delhi (IIT Delhi)
Hindi, English