People in DSML Kazakhstan

Senior Frontend Developer with 7+ years of experience specializing in React / React Native, Node.js. Proven track record of scaling complex web and mobile applications in fintech and e-commerce. Key results include optimizing app load times by 50% and achieving 85% test coverage in high-stakes environments. Expert in bridging the gap between UI/UX and backend services to deliver high-performance, user-centric products.

AI Research Engineer with ~4 years in ML/AI, focused on agentic systems that hold up in production. At Raiffeisenbank, I architected a multi-agent AI platform from scratch: autonomous agents generated product hypotheses, and 67% of them were accepted by product teams for testing. Earlier, I built an A/B testing framework whose experiments delivered a $25k monthly revenue uplift. Today I work on both sides of the field. At AIRI, I develop agentic VLM-based RAG for document understanding, currently outperforming published SOTA baselines. At HSE, I mentor graduate students in Advanced NLP, from Transformer internals to multi-agent systems. Before AI, I built my career in aviation rising from Maintenance Engineer to Production Manager of 60+ engineers in safety-critical operations. That is where my production-first mindset comes from: an AI system is only as good as its behavior under real-world constraints. Technical Stack: • Agentic & LLM: Agentic Workflows, LangChain, LangGraph, MCP, RAG, vLLM, Transformers • ML & Evaluation: Python, PyTorch, scikit-learn, Ragas, Experimental Design, A/B Testing, Drift Monitoring • MLOps & Orchestration: Apache Airflow, Kubernetes, Docker, CI/CD, MLflow • Data & Databases: PySpark, SQL, Hadoop, Vector DBs (Milvus), MongoDB, AWS S3 • Backend & Tools: FastAPI, Litestar, Kafka, RabbitMQ, Redis, Bash, Linux, Git, Pytest Open to roles: AI Research Engineer • LLM Engineer • Agentic AI Engineer • Applied Research Scientist

NLP Engineer / ML Engineer with 6+ years of commercial development experience. I build and ship end-to-end NLP & LLM solutions for production - from agentic AI assistants that take real actions across enterprise systems to multi-tenant RAG pipelines and high-scale NLP systems for fraud detection, search and content moderation. I know how to turn business goals into ML tasks, collect and label data, train and fine-tune models, and keep the whole pipeline healthy and measurable in production. I'm genuinely passionate about applied AI and how agentic systems are reshaping how businesses operate.

Aspiring Machine Learning Engineer (Data Science Major) with a proven track record in full-stack AI deployment, NLP, and Computer Vision. Experienced in fine-tuning LLMs, CNNs in PyTorch, and building FastAPI medical screening applications. Strong analytical foundation backed by 1,500+ solved competitive programming problems across various platforms.