Machine Learning Engineer (GCP, Vertex AI, Dataproc, Apache Iceberg) - W2 Only

About the Role

We are seeking a highly skilled Machine Learning Engineer to build, deploy, and manage scalable machine learning solutions on Google Cloud Platform (GCP). The successful candidate will operationalize machine learning models developed by Data Scientists, ensuring reliable execution, monitoring, performance optimization, and integration with enterprise data platforms. This role focuses on leveraging Vertex AI, Dataproc, Apache Spark, and Apache Iceberg to create production-grade ML pipelines capable of processing large-scale data and supporting advanced analytics and AI use cases.

Responsibilities

• Machine Learning Platform Engineering
  • Deploy, execute, and manage machine learning models provided by Data Scientists using Vertex AI.
  • Design and maintain automated ML pipelines for batch and near real-time scoring.
  • Configure and manage Vertex AI training, model registry, endpoints, and prediction services.
  • Monitor model execution, performance, latency, and operational health.
• Data Engineering & Processing
  • Develop scalable data processing frameworks using Dataproc, PySpark, and Spark SQL.
  • Build robust data ingestion, transformation, and feature engineering pipelines.
  • Optimize distributed processing workloads for performance and cost efficiency.
  • Ensure data quality, completeness, and consistency across ML workflows.
• Apache Iceberg Data Management
  • Design and manage large-scale data lakes using Apache Iceberg.
  • Implement partitioning, schema evolution, versioning, and time-travel capabilities.
  • Optimize Iceberg table performance for machine learning and analytical workloads.
  • Collaborate with data platform teams to establish enterprise data management standards.