Machine Learning Engineer GCP Vertex AI Apache Iceberg

IPolarity LLC; Whippany (NJ); On-site; USD 140,000 - 200,000; Full time

Job summary

IPolarity LLC is seeking a platform-oriented Machine Learning Engineer to bridge Data Science and Data Engineering on GCP. You will deliver scalable ML solutions, manage data pipelines, and implement MLOps for production-grade models.

The role emphasizes Vertex AI, Dataproc/PySpark, Iceberg, and cost-aware cloud optimization in a production environment.

Qualifications

• 7+ years of experience in ML engineering or data engineering.
• Strong experience with GCP and Vertex AI.
• Experience building distributed data and ML pipelines.
• Solid CI/CD and DevOps experience.

Responsibilities

• Deploy and manage ML models using Vertex AI.
• Build automated ML pipelines for batch and near real-time scoring.
• Develop scalable data processing pipelines with Dataproc and Spark.
• Design data lakes with Apache Iceberg and manage versioning.
• Implement MLOps, CI/CD, monitoring, and retraining workflows.
• Work with BigQuery and Google Cloud Storage.
• Monitor pipeline health, logs, metrics, and alerts.
• Optimize cloud resources and costs.

Skills

7+ yrs exp

GCP expertise

Vertex AI

Data engineering

ML pipelines

CI/CD

MLOps

Python

SQL

BigQuery

Tools

Vertex AI

Dataproc

Apache Spark

PySpark

Spark SQL

BigQuery

GCS

Docker

Kubernetes

Terraform

Job description

Machine Learning Engineer – GCP / Vertex AI / Dataproc / Apache Iceberg Location: Charlotte, NC. No OPT/CPT

Key Responsibilities

• Deploy and manage ML models using Google Vertex AI.
• Build automated ML pipelines for batch and near real-time scoring.
• Develop scalable data processing pipelines using Dataproc, Apache Spark, PySpark, and Spark SQL.
• Design and optimize large-scale data lakes using Apache Iceberg.
• Implement partitioning, schema evolution, versioning, and time-travel capabilities.
• Build data ingestion, transformation, and feature engineering workflows.
• Implement MLOps, CI/CD, model monitoring, retraining, and automation.
• Work with BigQuery and Google Cloud Storage (GCS).
• Monitor model performance, pipeline health, logging, metrics, and alerts.
• Optimize GCP compute resources and cloud costs.
• Support production incidents, reliability, security, and governance.

Required Skills

• 7+ years of experience in Machine Learning Engineering, Data Engineering, or related areas.
• Strong GCP experience.
• Hands-on Vertex AI experience.
• Dataproc.
• Apache Spark / PySpark / Spark SQL.
• Apache Iceberg.
• Python and SQL.
• BigQuery and GCS.
• Experience building distributed data and ML pipelines.
• Strong understanding of MLOps and ML model lifecycle management.
• CI/CD and DevOps experience.

Preferred Skills.

• Vertex AI Pipelines / Kubeflow Pipelines.
• Docker / Kubernetes.
• Feature Stores.
• Model Monitoring.
• Terraform / Infrastructure as Code.
• Data Governance / Metadata / Data Lineage.
• Financial Services, AML, Fraud, Risk Analytics, or regulated environments.

Ideal Candidate

We are looking for a platform-oriented Machine Learning Engineer who can bridge the gap between Data Science and Data Engineering and transform ML models into scalable, governed, production-ready solutions on GCP. If you have strong experience with GCP + Vertex AI + Dataproc/PySpark + Apache Iceberg + MLOps, we'd love to connect!