Summary
Majed Takieddine is a forward-deployed AI/ML engineer with nine years of experience building high-performance ML infrastructure and production systems across startups, fintech, marketplace, and nonprofit research environments. He has led large-scale GPU cluster launches and ML platform builds—most recently architecting end-to-end inference and training solutions for a 1024-H100 cluster at CZI and now working at Groq—focusing on reusable, scalable architectures and automation. Majed routinely bridges research and production: designing near-realtime ANN search platforms that handle millions of embeddings per minute, large-distributed reranking training on billions of examples, and low-latency GPU I/O optimizations. He pairs deep domain mastery with hands-on shipping ability under tight deadlines, mentoring teams and shipping production-grade services using modern tooling like Kubernetes, Triton, Vertex AI, and Polyaxon. Based in Chicago, he combines an industrial engineering background with relentless curiosity for new tools and a habit of turning complex constraints into elegant, pragmatic systems.
9 years of coding experience
7 years of employment as a software developer
Bachelor of Science (B.S.) Industrial Engineering with Computer Science Coursework Minor in Business Administration, Bachelor of Science (B.S.) Industrial Engineering with Computer Science Coursework Minor in Business Administration at University of Illinois Chicago
English, Arabic