MLOps Architect

Essential functions

• Design, build, and maintain scalable and reproducible ML pipelines using Vertex AI Pipelines (Kubeflow) and Cloud Composer (Apache Airflow).

• Operationalize ML models by deploying them via Vertex AI and managing lifecycle workflows using GCP Model Registry or MLflow.

• Monitor, troubleshoot, and optimize model performance and infrastructure using Cloud Monitoring, with a focus on reliability, latency, and uptime.

• Automate CI/CD workflows for ML systems using GitHub Actions, ensuring robust testing, versioning, and deployment of models and data pipelines.

• Integrate and maintain data pipelines using BigQuery, ensuring data availability, integrity, and compliance with ML requirements.

• Support experiment tracking and reproducibility through platforms like Vertex AI Experiments or MLflow, enabling structured A/B testing and iterative improvement.

• Collaborate with data scientists and engineers to implement and enforce modern MLOps best practices, including model versioning, artifact management, and governance.

• Integrate data quality tools (e.g., Great Expectations, TFDV) into ML pipelines to monitor and validate data inputs and outputs across the ML lifecycle.

• Contribute to the design and implementation of scalable and cost-effective MLOps architectures on Google Cloud Platform (GCP).

Qualifications

• Have hands-on experience designing and implementing modern MLOps practices.

• Proficient in using Vertex AI on Google Cloud Platform to build, train, deploy, and manage machine learning models.

• Worked with MLflow to track experiments, manage model versions, and streamline the lifecycle of machine learning projects from development to production.

• Strong experience with Google Cloud Platform services for data engineering and machine learning.

• Used Apache Airflow to orchestrate complex data and machine learning workflows.

• Have experience with Kubeflow.

Would be a plus

• Effective Teamwork

• Result orientation

• Reliability

We offer

• Opportunity to work on bleeding-edge projects
• Work with a highly motivated and dedicated team
• Competitive salary
• Flexible schedule
• Benefits package - medical insurance, sports
• Corporate social events
• Professional development opportunities
• Well-equipped office

About us

Grid Dynamics (NASDAQ: GDYN) is a leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services. Fusing technical vision with business acumen, we solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation. A key differentiator for Grid Dynamics is our 8 years of experience and leadership in enterprise AI, supported by profound expertise and ongoing investment in data, analytics, cloud & DevOps, application modernization and customer experience. Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.