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slavyolov

Slav Yolov

@slavyolov

Lead ML AI Engineer

Bulgarien
Englisch, Bulgarisch
Einige Informationen werden in englischer Sprache angezeigt.
Über mich
Senior Machine Learning Engineer with 10 years of experience building and productionizing data-driven solutions on Databricks, Azure, and MLflow. Strong hands-on background in lakehouse architectures, Spark-based pipelines, feature engineering, and scalable model deployment. Experienced in forecasting, operational optimization, and LLM-powered applications, with a track record of turning business requirements into production ML systems and measurable outcomes.... Mehr lesen

Kompetenzen

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slavyolov
Slav Yolov
offline • 
Durchschnittliche Antwortzeit: 1 Stunde

Meine Dienstleistungen

Maschinelles Lernen
I will senior machine learning engineer

Arbeitserfahrung

Confidentials

Lead ML & AI Engineer

Confidentials • Vollzeit

Feb 2025 - Present1 yr 3 mos

Company Name: Confidential (Hospitality & Gaming, US based) Joined a greenfield initiative to build an organization-wide ML/AI platform from day zero, with responsibility for leading two flagship products: an Offer Recommendation Engine on Databricks and a Talk-to-Your-Data interface on Snowflake Cortex ML. Partnered with leadership and engineering to define the architecture, drive planning, and deliver production-ready ML systems. Recently deployed the LLM-powered interface to production, while the recommender system is in final optimization phase.

Kaufland

DS / ML Engineer / Engineering Lead

Kaufland • Vollzeit

Jul 2017 - Mar 20257 yrs 8 mos

Company Name : Schwarz IT Bulgaria Progressed from Data Scientist to Engineering Lead, building and industrializing ML solutions for retail operations on Azure Databricks. Since 2023, led hands-on development and mentored 5+ team members, translating business needs into production ML systems and operational decision support. Core contributor on productionized solutions for supply chain optimization, intraday dynamic pricing for fruit and vegetables, VM anomaly detection, and others, using LightGBM, time-series forecasting, MLflow Model Registry, batch inference, and scalable Databricks/Azure pipelines.