DevOps Engineer
Core
Build and manage cloud infrastructure, CI/CD pipelines, and MLOps workflows to support application delivery, data pipelines, and production ML model deployment.
Role type
DevOps Engineer (MLOps focus)
Builds
Scalable cloud infrastructure, automated ML training/inference pipelines, and production ML model deployments
Domain
SaaS / Influencer Marketing / Cloud Infrastructure / Machine Learning
Deliverable
production ML models | infrastructure
Required skills
Kubernetes (EKS, Helm), AWS (SageMaker, EC2, S3), Terraform, CI/CD, GitOps, Python, SQL, GPU workload management, Airflow, MLflow, Prometheus, Grafana
Preferred skills
LLM deployment, BigQuery, CloudFormation, Postman
Technologies
Kubernetes, AWS, Terraform, SageMaker, Airflow, Kubeflow, Argo Workflows, MLflow, Prometheus, Grafana, BigQuery, Flask
Responsibilities
Design and maintain infrastructure for ML model training, validation, and deployment; Automate CI/CD pipelines for applications and ML workflows; Monitor model performance, latency, and data drift; Partner with data teams to support data pipelines and GPU workloads; Contribute to platform standards for infrastructure-as-code and observability.
Seniority
Mid-level (2-5 years experience)
