Profile
I have diverse experience as a data scientist and ML engineer, utilizing my analytical, statistical, and programming skills to collect, analyze, and interpret large data sets, and to build end-to-end AI solutions.
I have deployed actionable data-driven solutions, implemented impactful AI features, and solved multiple difficult business challenges. I hold a master's degree in AI and computer science. My wide range of technical competencies include statistics, deep learning, Bayesian optimization, reinforcement learning, NLP & LLMs, software engineering best practices, and cloud infrastructure & Kubernetes.
Experience
Senior ML Engineer
Living Homes January 2025 – Present
- Senior ML Engineer for the product's cognitive AI backend layer
- End-to-end feature development on multiple critical path features with product owners from user story and design to QA handover.
- Built an assortment of features such as: RL-based sleep environment optimization, statistics-driven sleep & health analysis, user voice ID recognition via deep learning, and LLM-driven natural language home automation and commands, multiple internal and external API integrations exposed as tools for the product's conversational AI agent.
- Python
- Azure
- PostgreSQL+MongoDB
- Docker
- Kubernetes
- Temporal
- LLMs
- Langchain
- RL
Senior Data Scientist & Team Lead
VMware Carbon Black June 2023 – September 2024
- Team Lead for the data team, encompassing data visualization, data engineering, and data science.
- Led collaborations between data teams, engineering, customer success, and product management teams to plan and deliver successful data projects for EDR product cost optimization and customer analytics.
- Python
- AWS
- GCP
- PostgreSQL
- Spark
- Tableau
Senior Data Scientist
VMware Carbon Black Sep 2021 – June 2023
- Senior Data Scientist specializing in the cybersecurity domain at Carbon Black.
- Built signature projects: cloud product cost monitoring and reduction in AWS, EDR ML-driven alerts, cost anomaly detection, LLMs for explainable alerting, and a customer churn model.
- Created cost monitoring tools, anomaly models, and governance methodologies to monitor Carbon Black's AWS & GCP cloud infrastructure costs at a granular level.
- Python
- PyTorch
- TensorFlow
- AWS
- GCP
- Terraform
- LLMs
- Langchain
Senior Data Scientist
Amplify Analytix LTD Jan 2018 – Aug 2021
- Senior Data Scientist specializing in delivering analytics to sales and marketing teams.
- Product Dev Lead for the first marketable product at Amplify Analytix on optimizing SEO using reinforcement learning.
- Python
- R
- Reinforcement Learning
- MySQL
- Tableau
ML Research Mentor
UCT, Cape Town July 2015 – Dec 2017
- Machine Learning Research Mentor for the Centre for Artificial Intelligence Research (CAIR) Lab internship program at the CSIR:
- Led research on the feasibility of robotic 3D space understanding, and new time-series forecasting models for financial markets.
- Python
- Machine Learning
- Time-Series Forecasting
Selected Projects
AI-based User Voice ID Recognition
AI-based user voice ID recognition for the Living Homes product.
- Built a voice ID recognition system that can identify users by their voice in near-real-time, and use that to personalize the user's experience.
- Achieved using fine-tuned Nvidia NeMo models.
- Python
- Azure
- Deep Learning
- AI
EDR ML-Driven & Explainable Alerting
Machine-learning alerting for endpoint detection and response (EDR), with LLM-based explanations to make alerts interpretable.
- Developed ML-driven alerting to improve detection signal in the EDR product.
- Applied LLMs to generate human-readable explanations for alerts.
- Python
- PyTorch
- LLMs
- Anomaly Detection
- Bayesian Methods
SEO Optimization via Reinforcement Learning
Amplify Analytix's first marketable product, optimizing SEO using reinforcement learning.
- Led product development from concept toward a marketable offering.
- Designed the reinforcement-learning approach driving SEO optimization.
- Python
- Reinforcement Learning
Skills
ML Methods & Stack
- TensorFlow
- PyTorch
- RL
- Bayesian Methods
- Langchain
- LLMs
Cloud & Infra
- GCP
- AWS
- Terraform
- Azure
- Docker
- Kubernetes
- Temporal
Data & Databases
- MySQL
- PostgreSQL
- MongoDB
- Spark
- Redis
- Neo4j
Education
Master of Science — Machine Learning and Artificial Intelligence
KU Leuven, Belgium
Bachelor of Science — Computer Science, Physics, and Mathematics
UCT, Cape Town
Languages
English — Native Proficiency
Bulgarian — Native Proficiency
Dutch — Intermediate
Danish — Intermediate
Publications
Gueorguiev, V., & Kuttel, M. (2016, September). Implementation, Validation and Profiling of a Genetic Algorithm for Molecular Conformational Optimization. In Proceedings of the Annual Conference of the South African Institute of Computer Scientists and Information Technologists (p. 16). ACM.