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# Senior Machine Learning Engineer, Nova Intelligence

- **Company:** Iterable, Inc.
- **Location:** Austin, TX, United States
- **Experience:** Expert
- **Salary:** $150,000 - $250,000
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Data Architecture, Software Debugging, Distributed Computing Environment, Python (Programming Language), Machine Learning, Operational Databases, Software Deployment, Feature Engineering, Apache Spark, Deep Learning, Backend, Kubernetes, Low Latency, Production Code, Machine Learning Operations, Data Pipelines, Databricks
- **Published:** November 8, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=a4445f0d2a0fae5e

## About the Role

* 5+ years of hands-on MLE experience putting complex models into production at scale.
 * Databricks & Spark mastery: Real experience building, optimizing, and scaling production data pipelines using Databricks.
 * Production-level Model Engineering: Proven track record of taking deep learning and ensemble architectures from training through optimization to production deployment.
 * Production Code: Strong Python and/or Scala skills with an emphasis on readable, modular, and maintainable systems code.
 * Systems & Infra Experience: Hands-on work with microservice backends, distributed compute (Ray/Spark), and containers (Kubernetes).
 * Pragmatism: You care more about serving latency, reliability, and measurable customer impact than novel theoretical architectures.

## Description

As a Senior Machine Learning Engineer at Iterable, you will design and build the end-to-end machine learning systems that power intelligence across our product. As a high-tech marketing platform, we work with thousands of large-scale and diverse enterprise customers. The scale and diversity of these workloads - supporting personalization with deep customizability - present unique and exciting challenges for machine learning at production scale.

You will have real autonomy: from research and experimentation through to models running reliably in production, you'll own the systems and models behind our ML products and help shape the direction of AI at Iterable., * Own the full model lifecycle end-to-end: EDA, feature engineering, distributed training, production deployment, latency monitoring, and online experimentation (e.g., multi-armed bandits, ensemble models).

 * Build and scale our data pipelines and serving architectures using Databricks, Spark, AWS, Ray, and Kubernetes.
 * Partner with Backend and Platform teams to elevate feature serving, improve overall data architecture, and establish engineering standards across the team.
 * Mentor engineers on the team and help set the technical direction for ML at Iterable., * Enhancing models that optimize send time and frequency of outgoing message campaigns.
 * Designing data pipelines that make it easy to implement and test new models.
 * Working with platform engineers to enhance our feature- and model-serving architecture.
 * Benchmarking and improving our multi-armed bandit implementation.
 * Building tools to visualize and debug features and models.