Mohammed Qudsi is an ML Infrastructure Engineer with 15 years of experience building cloud-native, DevOps, and SRE solutions, now focused on GenAI infrastructure at LipDub AI. He has designed and operated large-scale ML platforms on AWS and GCP using Kubernetes, Kafka, Spark, Flink, and Airflow, and built automated alerting and Python-driven tooling to improve cluster health and resource efficiency. His work at Infosys includes cost-saving cloud automation, CI/CD modernization, and production-ready ML model deployments, alongside research projects in quantum optimization and quantum ML. Mohammed combines hands-on engineering with training and mentoring experience, having published courses and guided interns through capstone projects. Based in Chicago with roots in Canada, he pairs an MTech in AI/ML with practical systems expertise that spans serverless architectures to real-time streaming. A less obvious strength is his hybrid background bridging bleeding-edge research (quantum computing) with pragmatic operational improvements that saved millions in compute costs.
15 years of coding experience
BITS Pilani, Birla Institute of Technology and Science
Bachelor of Engineering - BE, Bachelor of Engineering - BE at PES University
Certificate, Quantum Computing, Certificate, Quantum Computing at The Coding School
Contributions:3 releases, 2 reviews, 28 commits in 5 years 3 months
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Mohammed Qudsi - ML Infrastructure Engineer at LipDub AI