MLOps and AI Infrastructure Engineer with 3+ years of experience designing secure, scalable ML pipelines and cloud-native model deployment systems used in high-reliability environments, including financial-grade applicat…
MLOps and AI Infrastructure Engineer with 3+ years of experience designing secure, scalable ML pipelines and cloud-native model deployment systems used in high-reliability environments, including financial-grade applications.
Built automated MLOps pipelines with MLflow, CI/CD, and model versioning, enabling audit-ready and compliant deployments for fintech workloads.
Designed secure ML environments with IAM, encryption, and CloudTrail to meet BFSI-style governance.
Provisioned AWS ML infrastructure (EKS, S3, registries, endpoints) using Terraform.
Hardened clusters with RBAC, PodSecurity, Trivy, and Kube-bench.
Containerized and scaled inference via Docker + EKS HPA, boosting reliability by 50%.
Deployed FastAPI/MLflow model servers.
Built Prometheus–Grafana dashboards for latency, drift, and API health.
Reduced model deployment overhead by 60% through reusable templates and automation.
Built automated MLOps pipelines with MLflow, CI/CD, and model versioning for fintech workloads, Provisioned AWS ML infrastructure (EKS, S3, registries, endpoints) using Terraform, Deployed FastAPI/MLflow model servers and built Prometheus-Grafana dashboards
Developed a modular Kubeflow pipeline with preprocessing, training, evaluation, and auto-retraining. • Demonstrated strong competence in orchestrated ML workflows at scale. • Deployed models via KFServing, for strong orchestration and pipeline automation for production ML systems.
نظام التوظيف التشغيلي المعتمد على الذكاء الاصطناعي أولاً، الذي يوحّد ويؤتمت دورة التوظيف بالكامل للمؤسسات الحديثة حول العالم.
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