Global Applications Solution
GCP MLOps Engineer (Retail or E-commerce domain)
Global Applications Solution, Katy, Texas, United States, 77494
GCP MLOps Engineer (Retail or E-commerce domain)
Role: GCP MLOps Engineer (Retail or E-commerce domain)
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
Exposure to
DevOps or Data Engineering
environments.
Experience deploying ML solutions in
retail or e-commerce domains .
Seniority level Associate
Employment type Contract
Job function & Industries Consulting and Information Technology; IT Services and IT Consulting and Retail
#J-18808-Ljbffr
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
Exposure to
DevOps or Data Engineering
environments.
Experience deploying ML solutions in
retail or e-commerce domains .
Seniority level Associate
Employment type Contract
Job function & Industries Consulting and Information Technology; IT Services and IT Consulting and Retail
#J-18808-Ljbffr