Senior MLOps Engineer - Vertex AI on GCP

Cognizant; Georgia; Hybrid; USD 130,000 - 155,000; Full time

Benefits offered by this job

Medical Insurance

Dental Insurance

Vision Insurance

Life Insurance

Paid holidays

401(k)

Disability Insurance

Parental Leave

Employee Stock Purchase Plan

Job summary

Cognizant in Georgia seeks a Senior MLOps Engineer to design and manage the cloud infrastructure, deployment pipelines, and monitoring for ML models in production on Google Cloud. You will lead migrations to Vertex AI, build CI/CD pipelines with Vertex AI Pipelines, Kubeflow, Cloud Build, and implement governance and rollback strategies.

This hybrid role requires regular onsite presence in Atlanta, collaborating with Data Science and Data Engineering teams to deliver enterprise-grade MLOps

Qualifications

• 7+ years in data, software, or ML engineering.
• 3+ years building MLOps solutions and deploying models.
• Strong expertise with GCP services (Vertex AI, BigQuery, Cloud Storage, Pub/Sub).
• Proficient in Python and SQL; hands-on Docker, Kubernetes, and GKE.
• Experience with CI/CD and IaC (Terraform, GitHub Actions, GitLab CI, Jenkins, Cloud Build).
• Ability to lead initiatives and communicate with stakeholders.

Responsibilities

• Lead migration and deployment of ML models into Google Cloud Vertex AI ecosystem.
• Design and maintain scalable CI/CD/CT pipelines using Vertex AI Pipelines, Kubeflow, and Cloud Build.
• Develop model deployment frameworks for real-time and batch inference workloads.
• Establish monitoring and lifecycle governance including drift detection and model registry management.
• Collaborate with data science and data engineering teams to deliver enterprise MLOps solutions.

Skills

Team leadership

Cross-functional collaboration

Communication

Tools

Vertex AI

BigQuery

Cloud Storage

Pub/Sub

Terraform

GitHub Actions

GitLab CI

Jenkins

Cloud Build

Python

SQL

Docker

Kubernetes

GKE

Job description

Cognizant in Georgia seeks a Senior MLOps Engineer to design and manage the cloud infrastructure, deployment pipelines, and monitoring for ML models in production on Google Cloud. You will lead migrations to Vertex AI, build CI/CD pipelines with Vertex AI Pipelines, Kubeflow, Cloud Build, and implement governance and rollback strategies.

This hybrid role requires regular onsite presence in Atlanta, collaborating with Data Science and Data Engineering teams to deliver enterprise-grade MLOps