Overview
Skills
Job Details
We are seeking a skilled Google Cloud Platform (Google Cloud Platform) Cloud Architect with strong experience in designing and deploying scalable AI/ML solutions using Vertex AI. The ideal candidate will have deep hands-on knowledge of Google Cloud Platform cloud architecture, MLOps, and integrating AI models into production environments. You will work with cross-functional teams to modernize data infrastructure and deliver end-to-end machine learning pipelines.
Key Responsibilities:
Design and implement scalable, secure, and high-performing Google Cloud Platform-based cloud architectures.
Lead AI/ML solution architecture using Vertex AI, including model training, deployment, versioning, and monitoring.
Build end-to-end machine learning pipelines integrated with BigQuery, Cloud Storage, Cloud Functions, and other Google Cloud Platform services.
Enable MLOps best practices for continuous integration/continuous deployment (CI/CD) of ML models.
Collaborate with data scientists, ML engineers, and DevOps teams to bring AI models into production.
Conduct architecture reviews, cost optimizations, and performance tuning.
Define security, compliance, and governance frameworks for AI applications.
Mentor team members and drive Google Cloud Platform best practices across the organization.
Required Qualifications:
Bachelor s or Master s degree in Computer Science, Engineering, or related field.
8+ years of IT experience with 3+ years in Google Cloud Platform architecture.
Hands-on experience with Vertex AI, AutoML, and custom model training/deployment.
Strong knowledge of Google Cloud Platform services like BigQuery, Dataflow, Pub/Sub, Cloud Run, GKE, and Cloud Functions.
Experience with Kubeflow Pipelines, TensorFlow, or PyTorch on Google Cloud Platform.
Familiarity with infrastructure as code (Terraform, Deployment Manager).
Proficient in Python, SQL, and shell scripting.
Experience with MLOps tools and principles (CI/CD for ML, model registry, versioning, monitoring).
Google Cloud Platform Professional Cloud Architect or Machine Learning Engineer certification is preferred.
Preferred Skills:
Experience with real-time inference and streaming data pipelines.
Familiarity with hybrid or multi-cloud architectures.
Knowledge of data governance and model explainability in AI.
Experience working in regulated environments (finance, healthcare, etc.).
Certifications (Preferred):
Google Cloud Professional Cloud Architect
Google Cloud Professional Machine Learning Engineer