Lead MLOps Architect, GCP & Vertex AI Platforms

Quantiphi; Chicago (IL); On-site; USD 180,000 - 240,000; Full time

Job summary

Quantiphi is seeking a Senior MLOps Architect in Chicago to lead the architecture and delivery of large-scale ML/LLM pipelines on Google Cloud. You will guide cross-functional teams, define standards for monitoring, governance, and secure deployments across enterprise environments.

The role requires deep experience with Vertex AI, GKE and ML lifecycle management, plus mentoring of engineers on modern MLOps practices. Chicago-based, full-time role with cutting-edge AI initiatives.

Qualifications

• Deep proficiency with GCP native AI/ML stack and Vertex AI platforms.
• Hands-on ML lifecycle management from data to deployment.
• Experience building and operating MLOps/LLMOps pipelines.

Responsibilities

• Architect and implement the MLOps strategy aligned with proposals and roadmaps.
• Design enterprise ML/LLM pipelines including training, validation, deployment and CI/CD.
• Build container-oriented ML platforms (GKE-first) and evaluate orchestration tools.
• Implement hybrid MLOps + LLMOps workflows with governance and monitoring.
• Serve as technical authority across internal and client projects on GCP.
• Enable observability, drift detection and auditability in ML/LLM systems.
• Collaborate with data engineering, platform, DevOps and stakeholders to productionize solutions.
• Ensure security, governance and compliance for GCP services and workloads.
• Conduct architecture reviews and guide teams through implementations.
• Mentor engineers on MLOps tools and Vertex AI capabilities.

Skills

GCP AI/ML stack

Python

Cloud-native development

MLOps

Tools

Vertex AI

GKE

Cloud Functions

AutoML

Vertex AI Pipelines

BigQuery ML

Kubernetes

CI/CD (Cloud Build/Deploy)

Kubeflow

Airflow

MLflow

Seldon

OpenAI models

Anthropic models

Llama models

Prometheus/Grafana

Cloud Monitoring

Job description

Quantiphi is seeking a Senior MLOps Architect in Chicago to lead the architecture and delivery of large-scale ML/LLM pipelines on Google Cloud. You will guide cross-functional teams, define standards for monitoring, governance, and secure deployments across enterprise environments.

The role requires deep experience with Vertex AI, GKE and ML lifecycle management, plus mentoring of engineers on modern MLOps practices. Chicago-based, full-time role with cutting-edge AI initiatives.