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 .