Senior Vertex AI / MLOps Engineer (GCP, Python, Terraform)
- Job Title: Senior Vertex AI Engineer
- Location: Houston, TX
- Client: Cognizant / NRG Energy
Job Summary
We are seeking an experienced
Senior Vertex AI Engineer
with
7+ years of experience
to lead the design, development, and deployment of large-scale Machine Learning and AI solutions exclusively on
Google Cloud Platform (GCP)
. The role requires deep technical expertise in
Vertex AI
,
MLOps
, and end-to-end ML lifecycle automation. The engineer will own the solution architecture, provide hands-on implementation, and mentor junior engineers, focusing on operationalizing AI/ML initiatives using core GCP services.
Key Responsibilities
- MLOps Architecture: Architect and optimize MLOps pipelines for model training, validation, deployment, and monitoring.
- Vertex AI Development: Lead the development and deployment of scalable ML models using Vertex AI (Pipelines, Training Jobs, Feature Store, Model Registry, and Monitoring).
- GCP Integration: Integrate core GCP components suchs as BigQuery, Dataflow, Cloud Run, Pub/Sub, and Cloud Functions .
- Technical Leadership: Lead troubleshooting, performance optimization, and provide architectural guidance while mentoring team members.
- Governance: Implement best practices in versioning, CI/CD, and governance for ML workflows.
Required Skills & Experience
- Vertex AI & GCP (3+ years hands-on): Practical experience with Vertex AI Pipelines, Training Jobs, Feature Store, and Model Monitoring .
- ML Development: Proven expertise in Python with libraries like TensorFlow, PyTorch, or Scikit-Learn .
- MLOps & DevOps: Strong understanding of MLOps, CI/CD, Docker/Kubernetes , and IaC tools ( Terraform preferred ).
- Integration: Experience integrating ML APIs and REST endpoints into business applications.
- Certification: 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.