Building intelligent systems • ML pipelines • Scalable APIs • Production ML
From model training to deployment with performance, reliability, and clean code

i, I'm Sirojbek — an AI/ML engineer with 3+ years of backend development experience, specializing in building production-ready machine learning systems and scalable APIs. I bridge the gap between data science and engineering, shipping end-to-end ML solutions that solve real business problems.

• Current focus: Building ML-powered features and robust backends for enterprise systems
• Past highlights: Architected 40+ microservices; re-engineered legacy systems for 10x performance gains; currently applying ML to optimize business workflows

💻 Tech Stack: AI/ML & Data Science:

• Frameworks: PyTorch, TensorFlow/Keras, scikit-learn, XGBoost, LightGBM
• NLP & LLMs: Transformers (Hugging Face), LangChain, OpenAI API, spaCy
• Computer Vision: OpenCV, PIL, YOLO, CNNs
• MLOps: MLflow, Weights & Biases, DVC, model versioning
• Data: pandas, NumPy, Polars, Jupyter, data pipelines

Backend & APIs:

• Python: FastAPI, Django, Flask, asyncio, Celery
• ** Node js" Nest js , Express js , Jwt Web Socket
• PHP: Laravel 12, Symfony components, modern PHP 8.x
• APIs: REST, GraphQL, WebSockets, event-driven architectures

Infrastructure & Deployment:

• Databases: PostgreSQL (pgvector), MySQL, Redis, vector databases (Pinecone, Weaviate)
• Cloud & ML Platforms: AWS (SageMaker, Lambda, EC2, S3), Docker, Kubernetes
• Monitoring: MLflow tracking, Prometheus, Grafana, Sentry
• CI/CD: GitHub Actions, automated testing, model deployment pipelines