ML Platform Engineer - Production ML Pipelines

Zionsbancorp; Utah; Hybrid; USD 120,000 - 190,000; Full time

Benefits offered by this job

Health insurance

Paid time off

401(k) with company match

Tuition reimbursement

Job summary

Zions Bancorporation is seeking a Software Engineer, ML Platform to join its Enterprise Technology and Operations team in Utah. You will productionize ML applications at scale, build deployment pipelines, and develop real-time decisioning components with robust observability.

You will work in an Agile environment, focusing on model lifecycle, monitoring, and governance, while leveraging CI/CD for reliable deployments and cloud platforms like GCP.

Qualifications

• 6+ years of professional software engineering experience.
• Strong Python proficiency with tests and production-grade code.
• Experience with Docker and Kubernetes, container deployments.
• Experience building or maintaining CI/CD pipelines.
• Familiarity with cloud platforms (e.g., GCP) including IAM basics.
• Experience instrumenting production services with metrics and logging.
• Understanding of distributed systems concepts such as retries and idempotency.

Responsibilities

• Build and maintain deployment pipelines and containerized services.
• Develop real-time decisioning components and event processing.
• Implement observability with metrics, logging, tracing, and dashboards.
• Design model lifecycle: training pipelines, registry, versioning.
• Implement model monitoring for data quality and drift.
• Collaborate in an Agile team to connect data, decision logic, and services.
• Apply CI/CD best practices for ML models and app code.
• Ensure secure, governable ML with responsible/Explainable AI practices.

Skills

Python

Docker

Kubernetes

CI/CD

GCP

Metrics & Logging

Distributed Systems

ML Platform

Model Monitoring

Tools

MLflow

Kafka

Airflow

Dagster

Prefect

Databricks

Spark

Delta Lake

Job description

Zions Bancorporation is seeking a Software Engineer, ML Platform to join its Enterprise Technology and Operations team in Utah. You will productionize ML applications at scale, build deployment pipelines, and develop real-time decisioning components with robust observability.

You will work in an Agile environment, focusing on model lifecycle, monitoring, and governance, while leveraging CI/CD for reliable deployments and cloud platforms like GCP.