Sr. Data Engineer

Job Title: Sr. Data Engineer
Location: Charlotte, NC

Job Overview:
Lead and optimize the integration of machine learning models into business-critical applications using Google Cloud Platform Vertex AI. Collaborate with cross-functional teams to ensure robust model deployment, performance, and lifecycle management in production environments.

Key Responsibilities:

• Architect, design, and implement scalable, resilient, and secure model inference pipelines utilizing Vertex AI, Vertex Pipelines, and associated Google Cloud Platform services
• Enable seamless model deployment, versioning, monitoring, and rollback using Vertex AI Model Registry, Prediction Endpoints, and Model Monitoring
• Optimize model performance, throughput, and cost for high-load, real-time, and batch scenarios
• Automate all aspects of the model lifecycle: CI/CD pipelines, retraining, shadow testing, and operational troubleshooting
• Participate in architecture reviews and champion best practices in ML model orchestration, resource tuning, and observability

Top 3 Required Skills:

• Minimum 2 years strong experience with model integration, deployment, and scaling using Google Cloud Platform Vertex AI, including Pipelines, Endpoints, Model Monitoring, and Feature Store
• Expertise in production ML scaling: load balancing, low-latency optimization, A/B testing, and automated retraining
• Proficiency in MLOps, containerized environments, and infrastructure-as-code

Preferred Skills:

• Experience with MLOps tools: Kubeflow, MLFlow, or TFX
• Familiarity with ML observability: Prometheus, Grafana, Stackdriver
• Exposure to hybrid or federated deployment architectures

Software & Technical Skills:

• Google Cloud Platform Vertex AI Suite (Pipelines, Feature Store, Model Monitoring)
• Python (integration & automation frameworks)
• Git, Docker, Poetry, Terraform or Deployment Manager
• BigQuery, Dataflow, Cloud Functions
• Monitoring tools (Stackdriver, Prometheus, etc.)