Member Of Technical Staff - ML Research at Causal Labs
San Francisco, California, United States
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Summary
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Devashish Prasad is an ML researcher and engineer with eight years of experience building large-scale foundation models and production ML systems, currently developing AI physics models for weather prediction at Causal Labs. He holds an M.S. in Computer Science (ML) from Purdue and has a publication record including a highly cited CVPR paper and diffusion-model work from Kihara Lab. At Nabla Bio he helped design and scale a structural+sequence protein foundation model (JAM), running distributed training and inference across thousands of GPUs and delivering LLM-driven antibody optimizations that accelerated client lead discovery. His background spans computer vision, optical flow, and super-resolution at companies like Snap and Viasat, plus a string of research-to-production internships and hackathon finals with defense and industry partners. Comfortable moving models from research to GPU-cluster deployment, he combines deep generative modeling expertise with practical ML infra skills and a knack for squeezing 2–3× performance improvements out of systems. Based in San Francisco, he blends academic rigor with measurable biotech and geoscience impact—often on problems that require both physics intuition and scalable engineering.
7 years of coding experience
7 years of employment as a software developer
Bachelor's in Engineering Information Technology, Bachelor's in Engineering Information Technology at Pune Institute of Computer Technology
Master of Science - MS Computer Science, Master of Science - MS Computer Science at Purdue University
Diploma in Computer engineering Computer Science, Diploma in Computer engineering Computer Science at Government Polytechnic Pune
10th standard CBSE board, 10th standard CBSE board at Aaryan World School, Pune
Contributions:16 commits, 14 pushes, 1 branch in 10 days
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Devashish Prasad - Member Of Technical Staff - ML Research at Causal Labs