AI Automation Engineer

Job Requirement
Qualifications & Skills Must-Have:
0 to 3 years in engineering or MLOps roles, with hands-on experience building production workflows in GCP.
Deep experience with Vertex AI, Kubeflow Pipelines, or Kubeflow on GKE.
Proficiency in Python, Terraform (or comparable IaC tools), SQL.
Strong knowledge of GCP services: BigQuery, Dataflow, Pub/Sub, Cloud Functions, Cloud Storage, Secret Manager, IAM, KMS, VPC, etc.
Expertise in secure data workflows: encryption, compliance frameworks, identity and access management.
Experience implementing CI/CD automation for AI/ML systems.
Nice-to-Have:
Certifications such as Google Cloud Professional Data Engineer, Professional Cloud Architect, or MLOps Engineering Specialist.
Familiarity with Docker, Kubernetes, Kubernetes-native orchestration.
Knowledge of GitOps tooling: ArgoCD, Flux, or Jenkins X.
Experience with data cataloguing tools like Data Catalog, DataGov, Great Expectations, or similar.
Statistical understanding of model evaluation, drift detection, bias mitigation.
by R C W M A S Global
Role: Search Engineer
Industry Type: Internet
Department: Engineering - Software & QA
Employment Type: Full Time, Permanent
Role Category: Software Development

UG: Any Graduate
PG: Any Postgraduate