Hafizur Rahman

Senior MLOps Engineer at Kroll Canada Limited

Leveraged KServe ModelMesh for efficient multi-model serving to support concurrent deployment of multiple models with optimized resource utilization. Utilized MLflow for model management and Terraform to automate infrastructure provisioning, optimizing CPU/GPU endpoints and reducing latency. Enhanced observability with Databricks Lakehouse Monitoring and GitOps, implementing drift detection for model reliability. Automated ML workflows with Databricks Workflows, MLflow, and Azure DevOps, streamlining CI/CD/CT pipelines and enforcing governance.

Senior ML Engineer at Noze Inc.

Architected scalable platforms on GCP/AWS using Kubernetes, GitOps, and Terraform, establishing best practices for production and testing infrastructures. Collaborated with developers to address codebase gaps, enhancing AI model pipeline scalability, observability, and reliability. Developed MLOps processes for sensor data, improving prediction accuracy and deployment efficiency via denoising and anomaly detection. Optimized CI/CD pipelines, migrated infrastructure, reduced downtime by 60%, and improved reliability with robust monitoring.

ML Engineer at Konnect AI (Promark)

Deployed computer vision models on edge devices using GCP, Kubernetes, GitOps, and Terraform for scalable production environments. Developed ML solutions with time series forecasting, reducing production delays by 30% and improving operational efficiency.

Data Scientist (NLP) at DistillerSR

Built scalable web-scraping service on AWS with Terraform and GitOps, enhancing data pipeline observability and security. Deployed text classification models on AWS SageMaker (92.7% accuracy), integrating with CI/CD for production environments.