Summary
Amir Meimand is a Senior AI/ML Customer Engineer with a PhD in Operations Research and over a decade of hands-on experience building and deploying machine learning solutions across retail, fintech, and healthcare. He has led data science and ML architecture efforts at Google, Snowflake, and Salesforce, translating complex research into production-ready, cost- and security-conscious cloud deployments. Known for guiding cloud migrations and tailoring solutions to client constraints, Amir bridges technical depth with customer-facing partnership to ensure models deliver business impact. His background in operations research and optimization informs pragmatic approaches to model design, often yielding more efficient, interpretable solutions than black-box alternatives. Based in San Francisco, he combines academic rigor with product-focused engineering to democratize AI tools for broader user communities. Unexpectedly for a practitioner of scalable ML, he maintains a researcher’s lens—prioritizing principled solutions that reduce downstream operational risk.
8 years of coding experience
11 years of employment as a software developer
Amirkabir University of Technology
Doctor of Philosophy (PhD) Operations Research, Doctor of Philosophy (PhD) Operations Research at Penn State University