Senior MLOps Engineer (Real-Time Decisioning)
Core
Co-own MLOps practices to establish standards for model deployment, serving, scaling, and infrastructure efficiency, ensuring models support accurate ad selection through reliable production systems.
Role type
Senior MLOps Engineer (Real-Time Decisioning)
Builds
Automated pipelines for training, testing, and deployment; model-serving infrastructure; dashboards for performance and cost tracking.
Domain
Digital marketing / Commerce media / Cloud ML
Deliverable
production ML models
Required skills
Python, SQL, PySpark, Databricks, AWS, MLflow, Delta Live Tables, CI/CD, automated testing, monitoring systems, architecture design, production troubleshooting, code review, mentoring
Preferred skills
Data governance, security, compliance, model observability, explainability, stream processing, near-real-time pipelines, digital marketing metrics
Technologies
Databricks, AWS, Python, SQL, PySpark, MLflow, Delta Live Tables
Responsibilities
Partner with ML scientists to operationalize models; Build and optimize automated pipelines; Establish standards for versioning, testing, and release controls; Design and scale model-serving infrastructure; Lead investigations and resolve production issues; Create and maintain dashboards for tracking.
Seniority
Senior, hands-on technical leadership
