class MLEngineer:
def __init__(self):
self.name = "Nikolay Semikin"
self.role = "ML Engineer · Data Scientist · AI Agents Architect"
self.location = "Omsk, Russia"
self.education = "Fundamental Informatics & IT @ OmGTU"
self.focus = [
"Computer Vision",
"LLM Multi-Agent Systems",
"Data Science",
]
self.stack = [
"Python", "PyTorch", "LangGraph",
"Docker", "FastAPI", "PostgreSQL",
]
self.strengths = ["Clean Architecture", "Multiple AI Hackathon Wins 🏆"]
def current_mission(self) -> str:
return "Transforming data into reliable products using ML, CV, and NLP"- AI Agents: Designing and developing intelligent multi-agent systems and RAG pipelines using LangChain and LangGraph.
- Computer Vision: Building and deploying visual quality control systems.
- NLP & LLM: Optimizing local LLM inference architectures for dialogue quality assessment.
- MLOps & Backend: Containerizing ML components with Docker, designing REST APIs on FastAPI, optimizing PostgreSQL workflows, conducting A/B tests, and analyzing metrics with SQL.
- System Analysis: Designing data processing pipelines for unstructured data, auditing enterprise business processes, and writing technical specifications for ML-driven production automation.
Languages & Core
ML / AI / Agents
Data & Analytics
Infra & MLOps
