Role overview
*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
.
What you'll work on
- 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.
What we're looking for
- 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 .
Tags & focus areas
Used for matching and alerts on DevFound Contract Machine Learning Data Science Mlops Pytorch Tensorflow Data Engineer Ai