Summary
Alibek Kaliyev is a Machine Learning Engineer and software developer with 8 years of experience building production-scale ML and cloud systems, currently working on GenAI platforms after a series of founding-team roles at AWS where he shipped Amazon Quick Suite and Bedrock Knowledge Bases features. He blends strong research chops—from deploying physics-informed neural networks on FPGA with microsecond latency to GATs for clinical prediction—with pragmatic engineering work on APIs, CI/CD, testing frameworks, and load infrastructure that serve hundreds of thousands of users. Comfortable across Java, Python, TypeScript, and AWS, he has a track record of accelerating pipelines (e.g., 3.5x data extraction speedups) and shrinking models for edge deployment (3000x size reduction). A Lehigh CS & Business alum now pursuing MSCS at UT Austin, he also co-founded an AI/ML consulting firm and led student tech initiatives, reflecting a mix of product instincts, academic rigor, and operational delivery.
8 years of coding experience