Senior Vertex Engineer

Position: Senior Vertex AI Engineer Location: Houston, TX (Preferred) – Remote also considered About the Role: We are seeking an experienced Senior Vertex AI Engineer to lead the design, development, and deployment of large-scale machine learning and AI solutions on Google Cloud Platform (GCP). The ideal candidate should bring deep technical expertise in Vertex AI, MLOps, and end-to-end ML lifecycle automation — capable of owning solution architecture and mentoring junior engineers. Key Responsibilities: • Lead the development and deployment of scalable ML models using Vertex AI. • Architect and optimize MLOps pipelines for model training, validation, deployment, and monitoring. • Work closely with data scientists, solution architects, and DevOps teams to operationalize AI/ML initiatives. • Manage model lifecycle using Vertex AI Pipelines, Feature Store, and Model Registry. • Implement best practices in versioning, CI/CD, and governance for ML workflows. • Integrate GCP components such as BigQuery, Dataflow, Cloud Run, Pub/Sub, and Cloud Functions. • Lead troubleshooting, performance optimization, and production support for deployed ML services. • Provide architectural guidance and mentor team members in AI/ML engineering best practices. Required Skills & Experience: • 7+ years total experience in Data/ML Engineering with at least 3+ years hands-on in Vertex AI and GCP. • Proven expertise in Python, TensorFlow, PyTorch, or Scikit-Learn for model development. • Strong understanding of MLOps, CI/CD, Docker/Kubernetes, and IaC tools (Terraform preferred). • Practical experience with Vertex AI Pipelines, Training Jobs, Feature Store, and Model Monitoring. • Experience integrating ML APIs and REST endpoints into business applications. • Excellent problem-solving, debugging, and cross-functional communication skills. • Google Cloud ML Engineer or Architect certification highly preferred. Nice to Have: • Exposure to Generative AI / LLM integration using Vertex AI or PaLM API. • Experience working with data governance, model explainability, and bias detection tools. • Ability to collaborate with product teams for AI-driven solution design.