GCP MLOps Engineer (Retail or E-commerce Domain)

Role: GCP MLOps Engineer (Retail or E-commerce domain) Location: Katy, TX (Hybrid) Duration: 12+ Months (C2C/W2) Job Description: We are seeking a highly skilled GCP ML Ops Engineer to design, build, and manage scalable machine learning pipelines and production-grade infrastructure on Google Cloud Platform. The ideal candidate will have hands-on experience in GCP services, machine learning model deployment, CI/CD automation, and containerization. Key Responsibilities: • Build and manage end-to-end ML pipelines on GCP (data ingestion, model training, deployment, and monitoring). • Automate model training and deployment workflows using Vertex AI, Kubeflow, or Cloud Composer. • Implement CI/CD pipelines for ML models using Cloud Build, GitHub Actions, or similar tools. • Develop scalable data pipelines using BigQuery, Dataflow, and Pub/Sub. • Manage model versioning, logging, and performance tracking. • Collaborate with Data Scientists and Cloud Engineers to productionize ML solutions. • Ensure best practices in security, scalability, and cost optimization within GCP environments. Required Skills: • 3+ years of experience in GCP (must have hands-on experience with Vertex AI, BigQuery, Cloud Storage, Dataflow). • Strong experience with ML Ops tools (Kubeflow, MLflow, TFX, or Vertex Pipelines). • Proficiency in Python and experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn). • Strong understanding of CI/CD, Docker, Kubernetes, and Terraform. • Familiarity with monitoring tools (Stackdriver, Prometheus, Grafana). • Experience with API integrations, data versioning, and model lifecycle management. Nice to Have: • Google Cloud Certified (Professional Data Engineer or ML Engineer). • Exposure to DevOps or Data Engineering environments. • Experience deploying ML solutions in retail or e-commerce domains.