Senior Software Engineer – Machine Learning Systems

Job Description

Senior Software Engineer | Zions Bank

The Tone:
This is a Senior Software Engineer role at Zions Bank, located in Midvale, Utah, with a hybrid work schedule. Zions Bancorporation’s Enterprise Technology and Operations (ETO) team is dedicated to transforming the financial institution through a commitment to technology and innovation. This position is vital as the primary software engineering expert on a small Agile team, focused on designing, building, and maintaining production systems for machine learning applications. You will play a key role in shaping the technical foundation for the team’s data and machine learning initiatives for years to come.

The TL;DR
• Role: Full Time
• Location: Hybrid – Midvale, Utah, USA

• Team: Small Agile team dedicated to productionizing machine learning applications and systems at scale.
• Mission: Design, build, and maintain production systems that support the team’s data and machine learning initiatives.
• Tech Stack: Python, Java, Go, Kotlin, Docker, Kubernetes, Splunk, Grafana, Kafka, Airflow, Databricks, Spark, GCP, Terraform

What You’ll Actually Do
• Engineering Practice: Establish and evolve the team’s engineering practice, encompassing SDLC, CI/CD, testing, and containerization.
• Backend Services: Design, build, and operate reliable, scalable backend services and APIs to support production systems.
• System Reliability: Define reliability targets for production systems and design services to consistently meet these objectives.
• Architectural Decisions: Make and document architectural decisions, carefully balancing reliability, maintainability, and project timelines.
• CI/CD and Deployment: Build and maintain CI/CD pipelines, environments, and container-based deployment practices using tools like Docker and Kubernetes.

The Must-Haves
• Background: Senior-level professional specializing in software engineering, with core knowledge in building and operating production services and productionizing machine learning applications.
• Experience: 6+ years of professional software engineering experience, including building and operating production services. Hands-on experience with CI/CD pipelines and container-based deployment using Docker and Kubernetes. Experience instrumenting production services with metrics, structured logging, tracing, and alerting using tools such as Splunk or Grafana.
• Skills: Strong proficiency in at least one backend language such as Python, Java, Go, or Kotlin; solid understanding of API design and distributed systems fundamentals.
• Bonus: Exposure to machine learning systems or ML infrastructure; experience with streaming platforms like Kafka; experience with workflow orchestration or data platforms such as Airflow, Databricks, or Spark; experience in financial services or other regulated environments; experience with GCP and infrastructure as code tools such as Terraform.