Machine Learning Systems Engineer, Ads ML Platform
Core
Building scalable data infrastructure and feature management platforms to power Ads ML systems at scale.
Role type
Senior IC data infrastructure engineer (ML platform)
Builds
Batch and real-time feature management platforms, training set generation systems, and agentic ML workflows
Domain
Internet / Advertising / Machine Learning Infrastructure
Deliverable
production ML models
Required skills
Distributed data systems (Spark, Flink, Kafka, Ray, Airflow, Kubernetes, BigQuery), production service development, data pipeline engineering, API design, workflow systems, developer tools, observability, performance tuning, reliability engineering, cost optimization
Preferred skills
Intelligent automation, agentic workflows, MLOps workflows (feature engineering, training pipelines, experimentation, model deployment, online serving)
Technologies
Spark, PySpark, Flink, Kafka, Ray, Airflow, Kubernetes, BigQuery
Responsibilities
Design and build data infrastructure for large-scale feature and training set computation, transformation, and storage; Develop frameworks for batch and real-time features focusing on reliability and scalability; Build platform capabilities for feature governance including lineage tracking, validation, drift detection, and versioning; Partner with ML engineers to integrate feature engineering workflows into production systems; Build systems supporting automated feature discovery and lifecycle management; Contribute to operational excellence through observability and cost optimization
Seniority
Senior, hands-on IC
