Akil Ibrahim is a Software Engineer based in San Diego with 10 years of experience blending machine learning research and production-grade software automation. Currently at Google, he previously built automation workflows and monitoring dashboards at Teradata and developed log-parsing systems that turned operational data into actionable metrics. His research internship at Adobe produced a WWW'19 paper and a filed patent for a deep learning model that estimates causal effects for personalized ad targeting, outperforming strong baselines. He holds an MS in Computer Science with specialization in AI from UC San Diego (4.0) and a high-achieving BTech from IIT Roorkee, reflecting a strong theoretical foundation. Akil’s profile reflects a rare mix of causal ML research and hands-on automation delivery, able to move ideas from prototype and publication into scalable operational systems.
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