AL engineer

SKU0001-2
Professional Summary
Senior AI Engineer with 8+ years of experience designing, deploying, and scaling machine learning and AI systems in production. Specialized in LLM integration, deep learning, computer vision, NLP, and MLOps. Led distributed teams delivering AI-driven products for fintech, e-commerce, and healthtech clients across North America and Europe. Strong background in scalable cloud architectures (AWS/GCP), model optimization, and data engineering pipelines.

Core Competencies
  • Machine Learning & Deep Learning (PyTorch, TensorFlow)
  • Large Language Models (OpenAI API, LLaMA, RAG systems)
  • NLP & Computer Vision
  • MLOps (MLflow, Kubeflow, Docker, Kubernetes)
  • Distributed Systems & Microservices
  • Python (Advanced), FastAPI, Node.js (intermediate)
  • Cloud: AWS, GCP
  • Vector DBs (Pinecone, Weaviate, FAISS)
  • CI/CD & DevOps integration
  • Data Engineering (Airflow, Spark)

Professional Experience

Senior AI Engineer
Under NDA (Remote, Canada)
2022 – Present
  • Architected and deployed a Retrieval-Augmented Generation (RAG) platform serving 150k+ monthly users.
  • Led migration of ML workloads to Kubernetes, reducing infrastructure cost by 28%.
  • Designed LLM-based automation system improving internal processing speed by 40%.
  • Built scalable inference APIs (FastAPI + Docker + AWS ECS).
  • Mentored 6 ML engineers and conducted architecture reviews.

AI Engineer
Under NDA (Tashkent, Uzbekistan)
2019 – 2022
  • Developed fraud detection models (XGBoost, Deep Neural Networks) reducing false positives by 23%.
  • Built real-time ML pipeline processing 3M+ transactions/day.
  • Implemented MLOps practices (CI/CD for models, experiment tracking).
  • Designed customer NLP chatbot with intent classification and entity extraction.

Machine Learning Engineer
Under NDA
2017 – 2019
  • Built computer vision pipeline for industrial defect detection (CNN-based).
  • Improved image recognition accuracy from 78% to 93%.
  • Developed automated ETL pipelines for structured and unstructured datasets.

Key Projects
Enterprise LLM Assistant (2024)
  • Built private GPT-based assistant with document ingestion (RAG + vector search).
  • Integrated Pinecone vector DB and implemented prompt optimization framework.
AI-Powered Risk Scoring System
  • End-to-end ML lifecycle management.
  • Deployed REST microservice with <120ms inference latency.

Education
BSc in Computer Science
Tashkent University of Information Technologies
2013 – 2017
Certifications
  • AWS Certified Machine Learning – Specialty
  • Deep Learning Specialization (Coursera)

Languages
  • English – Fluent
  • Russian – Advanced
  • Uzbek – Native

Publications & Open Source
  • Contributor to open-source NLP toolkit (GitHub)
  • Speaker at regional AI conferences (Central Asia AI Summit)