Jobs → Engineering → Machine Learning Engineer

About the Role We are looking for a Machine Learning Engineer to join our team in Mountain View, CA. This role focuses on building and deploying machine learning models for insider-risk scoring and anomaly detection. Key Responsibilities • Build feature pipelines using EMR Serverless Spark and event streaming • Develop versioned, point-in-time-correct behavioral features • Manage feature definitions, registries, backfills, freshness, and drift monitoring • Train and evaluate models for insider-risk scoring and anomaly detection • Deploy models for batch and real-time inference • Implement LLM-based enrichment and model serving • Ensure model explainability through feature contributions and evidence links • Manage model retraining, versioning, monitoring, A/B testing, and rollbacks • Collaborate with data engineering and analytics teams Requirements • 10+ years of overall experience in production ML systems • Strong expertise in distributed data processing • Experience with feature engineering and end-to-end model lifecycle management • Strong production experience with Apache Spark / PySpark and Kafka • Hands-on experience in machine learning model training, evaluation, and deployment • Experience with gradient boosting, anomaly detection, sequence models, or graph models • Strong knowledge of feature stores and feature engineering pipelines • Experience with point-in-time joins, feature versioning, and training/serving consistency • Strong MLOps experience, including model registry, CI/CD, monitoring, and rollback • Strong programming skills in Python, PySpark, and SQL • Experience with Iceberg/Hive tables, Athena, or Databricks • Data profiling and telemetry analysis