Senior ML Engineer: Production-Scale Personalization AI

Iterable, Inc.; Denver (CO); On-site; USD 150,000 - 250,000; Full time

Job summary

Iterable, Inc. is seeking a Senior Machine Learning Engineer to design and build end-to-end ML systems powering our product intelligence for thousands of enterprise customers. You will own model lifecycle, from research to production, and scale data pipelines with modern ML infrastructure.

Join a growth-minded team that values ownership, transparency, and a strong emphasis on latency, reliability, and customer impact.

Qualifications

• 5+ years of hands-on MLE experience putting complex models into production at scale.
• Databricks & Spark mastery in production data pipelines.
• Experience taking deep learning and ensemble architectures from training to production.
• Strong Python and/or Scala with readable, modular code.
• Experience with microservice backends, distributed compute, and containers.
• Focus on serving latency and reliability over theoretical novelty.

Responsibilities

• Build and ship core product ML capabilities: send-time optimization, recommendations, and personalization.
• Own the full model lifecycle end-to-end: EDA, feature engineering, distributed training, deployment, latency monitoring, and online experiments.
• Build and scale data pipelines and serving architectures using Databricks, Spark, AWS, Ray, and Kubernetes.
• Partner with Backend and Platform teams to elevate feature serving and data architecture.
• Mentor engineers and help set the technical direction for ML at Iterable.

Skills

MLE experience

Python/Scala

Model deployment

Latency & reliability

Production ML

Tools

Databricks

Spark

AWS

Ray

Kubernetes

Job description

Iterable, Inc. is seeking a Senior Machine Learning Engineer to design and build end-to-end ML systems powering our product intelligence for thousands of enterprise customers. You will own model lifecycle, from research to production, and scale data pipelines with modern ML infrastructure.

Join a growth-minded team that values ownership, transparency, and a strong emphasis on latency, reliability, and customer impact.