Summary
Muaaz Salagar is a Senior Machine Learning Engineer based in the San Francisco Bay Area with a decade of experience building and scaling production ML and distributed systems. He currently works on Adobe Firefly’s image generation inference stack and content-safety pipelines, having previously optimized large-scale ML systems at Disney Streaming and low-latency text search, ranking, and KNN/HNSW solutions at Salesforce. His background spans backend and infrastructure engineering across companies like Dell EMC and John Deere, with hands-on expertise in non-blocking Java microservices, Terraform-backed AWS infra, and C++ systems work from earlier roles. He combines research-minded rigor from a Northeastern CS master’s with practical production focus, shipping latent-search and model-serving improvements that move prototypes to low-latency reality. Notably, he bridges model scaling and safety—working on Image4/4 Ultra/Image5 deployments—bringing an uncommon mix of storage, search, and generative-model inference experience to product-focused ML engineering.
10 years of coding experience
11 years of employment as a software developer
Bachelor of Technology (BTech), Computer Science, Bachelor of Technology (BTech), Computer Science at Walchand College of Engineering Sangli
Master's degree, Computer Science, Master's degree, Computer Science at Northeastern University