Hire Shovit R. - MLOps Engineer

* DevOps/MLOps Engineer owning the design and operation of production cloud and ML infrastructure at Deloitte. I build reliable, automated platforms and the pipelines that move both applications and ML models to production safely. * Platform & Infrastructure * Design and operate a production Kubernetes (EKS) platform running 10+ microservices, improving release reliability with rolling deployments, automated health checks, and self-healing. * Provision infrastructure as code with Terraform and Helm; cut DEV/QA/staging setup time 40% and eliminated manual configuration errors. * CI/CD, GitOps & DevSecOps * Built multi-stage CI/CD across Jenkins, GitHub Actions, and Azure DevOps with automated build, test, security-scan, and deployment gates on every merge. * Drove GitOps continuous delivery with ArgoCD — declarative deployments with automated drift detection and rollback. * Embedded DevSecOps (Trivy, SonarQube, OWASP Dependency-Check) into pipelines, catching vulnerabilities before production. * Designed blue-green deployments enabling zero-downtime releases. * MLOps & LLMOps * Engineered end-to-end ML pipelines with Kubeflow (data prep, training, evaluation, deployment) with artifact and metadata tracking. * Built KServe inference services for high-throughput, low-latency model serving; standardized experiment tracking and model versioning with MLflow. * Operationalized model training on AWS SageMaker and shipped self-service model-testing tooling with Gradio. * Developed LLM automation with LangChain and LangGraph. * Observability & Networking * Built Prometheus + Grafana monitoring and alerting, reducing mean issue-detection time 30%. * Designed networking and DNS routing (VPC, EC2, Route 53). * Stack: AWS, Kubernetes (EKS), Terraform, Docker, Helm, Jenkins, GitHub Actions, ArgoCD, KServe, Kubeflow, MLflow, SageMaker, Prometheus, Grafana, Python, Bash.