Ekrem Sarı

Ekrem is an AI Researcher and Data Analyst at AIMultiple. He designs and runs hands-on benchmarks for AI and LLM systems.

Professional Experience

At AIMultiple, Ekrem benchmarks end-to-end AI systems and builds the data workflows and dashboards used to track benchmark and product metrics. His benchmarks cover embedding and reranker models, vector and graph databases, inference engines, quantization, GPU concurrency and multi-GPU scaling, cloud GPU pricing and providers, text-to-SQL, and RAG and agentic RAG frameworks.

Before AIMultiple, he worked as an Assessor at Yandex, where he evaluated search quality and labeled large volumes of data against detailed guidelines to support ranking and model quality.

Research Interest

Ekrem's work focuses on the MLOps and LLMOps lifecycle and on measuring the performance of AI systems. He compares models, frameworks, and infrastructure on metrics such as accuracy, throughput, API cost, and scalability, across the stack from embedding models and vector databases to GPU and cloud infrastructure. His MSc thesis automates systematic literature reviews with a RAG-based pipeline.

Education

Ekrem holds a BA from Hacettepe University and is completing an MSc at Başkent University.