Jobs via Dice
MLOps Engineer Google Cloud Platform Vertex AI
Jobs via Dice, Alpharetta, Georgia, United States, 30239
Overview
We are looking for an experienced
MLOps Engineer with strong Google Cloud Platform and Vertex AI expertise
to design and manage scalable ML pipelines and operationalize AI/ML solutions in production. The ideal candidate will work closely with Data Scientists, ML Engineers, and DevOps teams to build a robust
end-to-end MLOps ecosystem
on Google Cloud. Responsibilities Build, deploy, and optimize ML pipelines using Vertex AI Pipelines, Kubeflow, or TFX. Automate ML workflows including data ingestion, training, evaluation, deployment, and monitoring. Implement model versioning, feature store management, and experiment tracking. Integrate CI/CD pipelines for ML workloads using Cloud Build, Jenkins, or GitHub Actions. Deploy ML models to GKE, Cloud Run, or Vertex AI Endpoints for online/batch serving. Monitor model performance, drift, bias, and data quality in production. Work with Terraform/IaC to build scalable and secure Google Cloud Platform environments. Collaborate with Data Scientists to ensure reproducibility, governance, and compliance.
Required Skills & Experience
Hands-on expertise with Google Cloud (Vertex AI, BigQuery, Dataflow, Pub/Sub, Cloud Functions, GKE). Strong background in MLOps lifecycle management and ML model deployment. Proficiency in Python (ML frameworks: TensorFlow / PyTorch / Scikit-learn). Experience with CI/CD automation and DevOps tooling. Solid understanding of Docker, Kubernetes, Helm charts. Knowledge of observability tools (Stackdriver, Prometheus, Grafana). Familiarity with ML monitoring & governance frameworks.
Preferred Qualifications
Google Cloud Platform Professional Machine Learning Engineer or Professional Cloud DevOps Engineer certification. Experience with MLflow, Feast (feature store), A/B testing, and model monitoring frameworks. Strong understanding of data governance, security, and compliance in AI systems.
Why Join Us?
Build next-gen AI/ML solutions on Google Cloud. Be part of a high-performing, cross-functional team. Growth path towards MLOps/AI Platform Architect role.
Job Details
Seniority level: Mid-Senior level Employment type: Full-time Job function: Engineering and Information Technology Industries: Software Development
Location: Alpharetta, GA #J-18808-Ljbffr
We are looking for an experienced
MLOps Engineer with strong Google Cloud Platform and Vertex AI expertise
to design and manage scalable ML pipelines and operationalize AI/ML solutions in production. The ideal candidate will work closely with Data Scientists, ML Engineers, and DevOps teams to build a robust
end-to-end MLOps ecosystem
on Google Cloud. Responsibilities Build, deploy, and optimize ML pipelines using Vertex AI Pipelines, Kubeflow, or TFX. Automate ML workflows including data ingestion, training, evaluation, deployment, and monitoring. Implement model versioning, feature store management, and experiment tracking. Integrate CI/CD pipelines for ML workloads using Cloud Build, Jenkins, or GitHub Actions. Deploy ML models to GKE, Cloud Run, or Vertex AI Endpoints for online/batch serving. Monitor model performance, drift, bias, and data quality in production. Work with Terraform/IaC to build scalable and secure Google Cloud Platform environments. Collaborate with Data Scientists to ensure reproducibility, governance, and compliance.
Required Skills & Experience
Hands-on expertise with Google Cloud (Vertex AI, BigQuery, Dataflow, Pub/Sub, Cloud Functions, GKE). Strong background in MLOps lifecycle management and ML model deployment. Proficiency in Python (ML frameworks: TensorFlow / PyTorch / Scikit-learn). Experience with CI/CD automation and DevOps tooling. Solid understanding of Docker, Kubernetes, Helm charts. Knowledge of observability tools (Stackdriver, Prometheus, Grafana). Familiarity with ML monitoring & governance frameworks.
Preferred Qualifications
Google Cloud Platform Professional Machine Learning Engineer or Professional Cloud DevOps Engineer certification. Experience with MLflow, Feast (feature store), A/B testing, and model monitoring frameworks. Strong understanding of data governance, security, and compliance in AI systems.
Why Join Us?
Build next-gen AI/ML solutions on Google Cloud. Be part of a high-performing, cross-functional team. Growth path towards MLOps/AI Platform Architect role.
Job Details
Seniority level: Mid-Senior level Employment type: Full-time Job function: Engineering and Information Technology Industries: Software Development
Location: Alpharetta, GA #J-18808-Ljbffr