Highly skilled Cloud DevOps-AI Engineer with expertise in designing and managing scalable, secure, and automated cloud infrastructures to support AI-driven applications and enterprise workflows. Experienced in CI/CD pipelines, containerization, orchestration, and infrastructure as code, ensuring efficient model deployment and operational excellence. Proficient in developing and optimizing machine learning models with a focus on deep learning, natural language processing, and system automation. Passionate about integrating emerging technologies to enhance reliability, scalability, and productivity across cloud environments.
- AI/ML: PyTorch, TensorFlow, Scikit-learn, Transformers, Deep Learning, LLMs, NLP, RAG, Keras, LoRA, QLoRA, Hugging Face, Vector Databases, Prompt Engineering, Model Deployment, LangChain
- Data Management: Apache Airflow, Hadoop, Hive, MLflow, PySpark, ETL, SQL, FAISS, ChromaDB, Supabase
- Cloud: AWS, Azure, GCP
- Programming Languages: Python, Golang, C++, Shell, PowerShell, Javascript
- Infrastructure as Code (IaC): Terraform, Terragrunt
- Continuous Integration/Continuous Deployment (CI/CD): GitHub Actions, Azure DevOps, Jenkins
- Containerization and Orchestration: Kubernetes, ArgoCD, GitOps, Docker, Helm
- Monitoring and Logging: Prometheus, Grafana
- Version Control: Git, GitHub, BitBucket
- Web Servers: Nginx
- Operating Systems: Linux (Ubuntu, Red Hat, Amazon Linux, CentOS), Windows
Follow my projects here on GitHub. I'm always open to discussing new ideas, technologies, or collaboration opportunities!