👋 I'm a Machine Learning Engineer with 6 years of experience driving impactful results through data-driven solutions. I specialize in developing and deploying high-performance machine learning models for various applications, including recommender systems, user acquisition optimization, LLM-powered applications, audio processing, and search algorithms.
- Scaled the machine learning team from 4 to 12 members to meet the demand for personalized products
- Led engineering teams of up to 12, owning the full software development lifecycle from concept to production
- Employ a systems approach to software development, resulting in a 50% acceleration of business value delivery
- Led the development of the ML backend for a new product, achieving a significant growth in user listening time. Here are some announcements of product launch:
- Repo with RecSys toy example showcase my approach.
- Authored machine learning models for advertising and user acquisition, resulting in a 10% ROI increase.
- Built and deployed a production-ready AI data processing service that cut customer support costs by 70%.
- Conducted applied research of LLMs and Generative AI for 3 company business processes.
- Delivered a audio processing pipeline for large-scale musical tracks processing using Airflow, leading to improvement in users' spent time.
- Programming & Scripting: Python, SQL, Bash
- Machine Learning & AI: PyTorch, XGBoost, Scikit-Learn, MLFlow, OpenAI, Google GenAI, LlamaIndex
- Big Data & Databases: PostgreSQL, BigQuery, Apache Kafka, Qdrant, Redis, Clickhouse, DataBricks
- Cloud & DevOps: AWS, GCP, Docker, Kubernetes, TeamCity, Airflow, Prefect
- Software Engineering: API development, CI/CD, microservices architecture
- Tools & Frameworks: FastAPI, Flask, Git
- Monitoring & Observability: Prometheus, Grafana, Sentry, Logfire
I'm always open to discussing new opportunities and collaborating on exciting projects. Feel free to reach out on LinkedIn or schedule a quick chat via Calendly.