Summary
Yegór Kryukov is a seasoned Senior Lead Machine Learning Engineer with eight years of experience building enterprise-grade GenAI platforms and ML tooling, currently based in Washington, DC. At Capital One he designed and secured approval for a Guardrails SDK, led a company-wide GenAI SDK ecosystem that cut time-to-first-call from days to seconds, and architected a modality-agnostic embeddings engine that reduced training timelines from months to days. He has a strong track record delivering high-impact ML products across finance, government, and public-sector consulting—contributing to fraud/scam detection, RAG deployments, semantic search, and an FDA surveillance pipeline processing thousands of documents daily. Yegór blends deep engineering (PyTorch Lightning, Kubeflow, SageMaker) with platform thinking, mentorship, and product-focused innovation, including a filed patent for agentic SDK generation. Past roles show a pattern of technical leadership in constrained environments and measurable operational gains—from automating call centers to scaling national disease surveillance systems—demonstrating rare cross-domain fluency beyond core ML.
8 years of coding experience
18 years of employment as a software developer
Data Analytics, Data Analytics at The George Washington University
B.S., Computer Science and Information Technologies, 81, B.S., Computer Science and Information Technologies, 81 at Tashkent University of Information Technologies
Russian, English