Elkhan Dadashov is a software engineer with 10 years of experience building exabyte-capable data platforms and GenAI infrastructure, now contributing to Meta’s AI Platform from San Francisco. He has led design-to-production efforts for trillion-event-per-day streaming architectures and interactive ML platforms at Apple, Uber, and Salesforce, combining deep distributed-systems expertise (Flink, Spark, Iceberg, Kubernetes) with hands-on SDK and cloud service development. Elkhan’s strengths span real-time streaming, batch processing, and scalable dataset generation for ML, and he’s presented on interactive streaming infrastructure and platform design at industry conferences. Equally comfortable mentoring teams and shipping low-level infra, he has a track record of aligning technical roadmaps with product adoption—evident in Text2SQL and interactive analytics work. His academic background across Brown, Stanford SCPD, Stuttgart, and KAIST underpins a practical-research approach to complex system design. Notably, he has engineered solutions for unusually large record sizes and high-throughput sensor pipelines, reflecting a knack for solving non-standard scaling challenges.
10 years of coding experience
7 years of employment as a software developer
Bachelor of Science (B.Sc.) Computer Science, Bachelor of Science (B.Sc.) Computer Science at Korea Advanced Institute of Science and Technology
Master’s Degree Computer Science, Master’s Degree Computer Science at Brown University
Master's Degree Information Technology with specialization in Computer Software/Hardware Engineer, Master's Degree Information Technology with specialization in Computer Software/Hardware Engineer at University of Stuttgart
SCPD Artificial Intelligence Computer Science, SCPD Artificial Intelligence Computer Science at Stanford University
CS224N Final Project: Detecting if 2 questions are duplicates of each other.
Contributions:39 commits, 4 PRs, 8 pushes in 1 year 10 months
pythondetectingcs224nduplicates
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