Software Engineer, ML Platform

Zions Bancorporation’s Enterprise Technology and Operations (ETO) team is transforming what it means to work for a financial institution. With a commitment to technology and innovation, we have been providing our community, clients and colleagues the best experience possible for over 150 years. Help us transform our workforce of the future, today.

We are seeking a Software Engineer, ML Platform to join Zions Bancorporation.  In this role you will be part of an Agile team dedicated to product ionizing machine learning applications and systems  will be involved in the detailed technical design, development, and implementation of machine learning applications using both existing and emerging technology platforms. You'll focus on building and maintaining foundational components of the team’s ML platform and ensuring availability and performance of our ML services.

You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering and model development.

The Software Engineer, ML Platform will:

The Software Engineer, ML Platform draws from many disciplines, such as Operations, Modeling, and Data Engineering. In this role, you'll be expected to perform many backend and ML engineering activities, including one or more of the following:

Build and maintain deployment pipelines, environments, and containerized services for the team’s production systems.

Develop components of real-time decisioning services, including event processing, integrations, and decision logging.

Implement observability: metrics, logging, tracing, alerting, and dashboards for production services.

Design and maintain the model lifecycle: training pipelines, experiment tracking, model registry, versioning, and promotion from staging to production.

Implement model monitoring: prediction drift, feature drift, data quality checks, performance against labeled outcomes.

Collaborate as part of a cross-functional Agile team to create clean interfaces between data, decision logic, and services.

Leverage CI/CD best practices to ensure successful deployment of ML models and application code.

Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI.

Required Qualifications:

6+ years of professional software engineering experience building and operating production services.

Proficiency in Python, including testing, packaging, and production-quality code.

Experience with Docker and container-based deployment; working knowledge of Kubernetes.

Experience building or maintaining CI/CD pipelines.

Familiarity with cloud platforms (e.g. GCP), including IAM, networking, and storage basics.

Experience instrumenting production services with metrics, structured logging, and alerting, using tools such as Splunk or Grafana.

Understanding of distributed systems fundamentals such as retries, idempotency, and failure handling.

Preferred Qualifications:

Exposure to MLOps tools such as MLflow, feature stores, or model serving frameworks.

Experience with streaming platforms like Kafka.

Experience with workflow orchestration tools such as Airflow, Dagster, or Prefect.

Experience with Databricks, Spark, or Delta Lake.

Familiarity with rules engines or policy frameworks.

Visa Sponsorship:

This position is currently not eligible for employment visa sponsorship (e.g., H-1B visa). This includes, for example, situations where a candidate may have temporary work authorization while enrolled in school or upon graduation (e.g., CPT, OPT) but would need H-1B visa sponsorship within a few years of employment in order to maintain employment eligibility.

Location:

This position has a hybrid work from home…