Sergei Aleshkin

Rebuilt event-driven architecture (Kinesis, Glue, PySpark). Automated ML pipeline: Spark features, MLflow versioning, Airflow orchestration. Built data quality gates (anomaly detection) before model training. Monitoring for data drift and prediction drift. Stack: AWS, Airflow, MLflow, Spark, Data Governance.

Senior AI Lead with 10+ years deploying production ML systems at scale. Expert in LLM orchestration, generative AI, MLOps infrastructure, and responsible AI governance. Built 20+ production systems: recommendation engines, RAG/agent systems, forecasting models, optimization solvers. Leads technical teams, mentors engineers, presents AI strategy to C-level. Deep expertise with Azure AI Foundry, Azure OpenAI, LangChain, MLflow, Databricks.

Data analysis, text analysis, automation, interactive reports - html5 presentations and dashboards, predictive analytics, working with mobile data to make investment decisions. Developing big data infrastructure and running ML models with reports – worked both with IT and business. Some projects: client clustering, identification of risky clients, next best offer, topic modeling, processes optimization.

Processes automation and optimization, what if analysis, tracking performance of strategies and models and their validation, creating KPI, BRD, BI. Created tool to optimize number of bank’s employees – C# applications with ML backend.

Computational finance

Mathematics, data science