Description

  • Led evolution of data-focused projects from Data Engineering/Data Science into advanced MLOps roles.
  • Spent 80% of time on hands-on development and 20% on architectural tasks under senior architects, acquiring practical architecture skills.
  • Over 7 years of Python and 3 years of TypeScript development experience.
  • Documented architecture, workflows, and best practices for knowledge sharing and compliance.
  • Provided technical oversight and established guidelines for team members.
  • Implemented end-to-end MLOps and LLMOps pipelines using Azure Machine Learning and Azure OpenAI.
  • Designed scalable infrastructure for training, deployment, and monitoring of ML/LLM models in production environments.
  • Collaborated with data scientists and engineers to optimize model development, testing, and deployment processes.
  • Managed Azure Kubernetes Service (AKS) clusters and containerized machine learning workloads.
  • Ensured model governance, versioning, and reproducibility using MLflow and Azure DevOps.
  • Advocated for and integrated DevSecOps practices to ensure security and compliance throughout the ML lifecycle.
  • Monitored, troubleshot, and maintained production ML systems to guarantee high availability and performance.
  • Demonstrated experience with Azure Machine Learning, Azure OpenAI, Azure DevOps, and AKS.
  • Proficient in Python, Docker, Kubernetes, and CI/CD pipeline implementation.
  • Experienced in LLM fine-tuning, prompt engineering, and model deployment.
  • Familiar with MLflow, Terraform, and monitoring tools such as Prometheus/Grafana

Key Skills
Education

Any Gradute

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