🧑‍💻

Curriculum Vitae

Your Name

Software Engineer · DevOps · MLOps

Your City, Country you@email.com GitHub LinkedIn

Education

Qualifications

Degree

Bachelor's in Computer Science

University Name

2016 — 2020

Certification

AWS Solutions Architect — Professional

Amazon Web Services

2022

Certification

Certified Kubernetes Administrator (CKA)

Cloud Native Computing Foundation

2023

Experience

Work History

Senior DevOps Engineer

Company Name

2024 — Present · Remote

Designed and maintained Kubernetes clusters across 3 cloud providers. Built GitOps pipelines with ArgoCD reducing deployment time by 70%. Implemented observability stack with Prometheus, Grafana, and Loki.

KubernetesArgoCDTerraformAWSPrometheus

MLOps Engineer

Company Name

2022 — 2024 · On-site

Built end-to-end ML pipelines using Kubeflow and Apache Airflow. Reduced model training time by 40% through distributed training on GPU clusters. Managed model registry and A/B testing infrastructure.

KubeflowAirflowPythonMLflowGCP

Software Engineer

Company Name

2020 — 2022 · Hybrid

Developed microservices in Go and Python, serving 2M+ requests/day. Led migration from monolith to event-driven architecture using Kafka. Wrote CI/CD pipelines and improved test coverage from 40% to 85%.

GoPythonKafkaDockerPostgreSQL

Senior DevOps Engineer

Company Name

2024 — Present · Remote

Designed and maintained Kubernetes clusters across 3 cloud providers. Built GitOps pipelines with ArgoCD reducing deployment time by 70%. Implemented observability stack with Prometheus, Grafana, and Loki.

KubernetesArgoCDTerraformAWSPrometheus

MLOps Engineer

Company Name

2022 — 2024 · On-site

Built end-to-end ML pipelines using Kubeflow and Apache Airflow. Reduced model training time by 40% through distributed training on GPU clusters. Managed model registry and A/B testing infrastructure.

KubeflowAirflowPythonMLflowGCP

Software Engineer

Company Name

2020 — 2022 · Hybrid

Developed microservices in Go and Python, serving 2M+ requests/day. Led migration from monolith to event-driven architecture using Kafka. Wrote CI/CD pipelines and improved test coverage from 40% to 85%.

GoPythonKafkaDockerPostgreSQL

Projects

Selected Work

01

MaaS — Monitoring as a Service

SaaS platform that gives clients a Grafana dashboard for all their cloud VMs without installing agents on every machine. One Docker container per VPC, outbound WSS connection, automatic VM discovery.

FastAPINext.jsKubernetesPrometheusGrafanaOracle DB

02

ML Pipeline Orchestrator

End-to-end MLOps platform for training, versioning, and serving models. Supports distributed training on GPU clusters, experiment tracking, and automated rollout with traffic splitting.

KubeflowMLflowPythonKafkaRedis

03

GitOps Bootstrap Toolkit

Terraform + Helm toolkit that provisions a production-ready Kubernetes cluster with ArgoCD, Prometheus stack, Ingress, and Sealed Secrets in under 10 minutes.

TerraformHelmArgoCDGitHub ActionsAWS EKS

Skills

Tech Stack

PythonGoTypeScriptBashKubernetesDockerTerraformHelmCI/CDGitHub ActionsArgoCDJenkinsMLflowKubeflowApache AirflowFeastAWSGCPOracle CloudPrometheusGrafanaLokiOpenTelemetryPostgreSQLRedisKafkaMongoDB