Summary
Akshit Tyagi is a machine learning engineer with a decade of experience building research-driven ML systems across healthcare, perception, and low-power edge applications in the San Francisco Bay Area. He has transitioned from internships at NVIDIA and Amazon into research and applied roles at Google Research/DeepMind, Helm.ai, and startup environments, now serving as a founding member of technical staff at Axiom Bio. His work spans training and fine-tuning foundation models (UNets, latent diffusion, DinoV2), tabular and EHR modeling for clinical insights, generative simulation for augmented data, and on-device optimization for constrained hardware. He has a strong academic foundation from IIT Delhi and UMass Amherst and brings practical production experience—deploying models to batch scoring and improving model stability in clinical settings. Notably, he combines deep research instincts with hands-on ML engineering, using weak supervision and out-of-distribution techniques to reduce maintenance overhead in drifting systems. He is active in the Bay Area AI scene and maintains a personal site showcasing his projects and experiments.
10 years of coding experience
4 years of employment as a software developer
Indian Institute of Technology Delhi (IIT Delhi)
Master of Science - MS Computer Science, Master of Science - MS Computer Science at University of Massachusetts Amherst
High School Sciences , High School Sciences at Delhi Public School - R. K. Puram
English, Hindi, Sanskrit