Tim Ganiev is a research engineer and machine learning specialist with nine years of experience building and productionizing NLP and alignment systems across startups and larger organizations. He has led teams and shipped measurable improvements—designing safety classifiers and red-teaming pipelines that dramatically increased rejection rates while reducing false negatives, and optimizing distributed LLM serving to cut tail latency by ~40%. His background spans end-to-end ML work from active learning and toxic-content classification to model compression and adversarial robustness, with notable impact at Replika and Sberbank. Based in Yerevan, he combines research rigor with product-minded engineering, often co-designing instrumentation and frontend/back-end integrations to turn alignment research into A/B-testable features. A pragmatic tinkerer early in his career as a .NET developer, he brings both systems-level optimization skills and applied ML research to bear on real-world conversational AI problems.
9 years of coding experience
8 years of employment as a software developer
Bachelor's degree, Computer Science, Bachelor's degree, Computer Science at Kazan National Research Technical University named after A.N.Tupolev – KAI
Contributions:3 releases, 18 commits, 14 PRs in 9 months
nlppytorchpythonseq2seqdeep-learning
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