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Iterable

Real-time cross-channel customer engagement platform

Senior Machine Learning Engineer

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeLisbon, PortugalHybrid

About the Job

Requirements

  • At least 5 years of hands-on machine learning engineering experience putting complex models into production at scale.
  • Experience building, optimizing, and scaling production data pipelines using Databricks.
  • A proven track record of taking deep learning and ensemble architectures from training through optimization to production deployment.
  • Strong Python and/or Scala skills, with an emphasis on readable, modular, and maintainable systems code.
  • Hands-on experience with microservice backends, distributed computing such as Ray or Spark, and containers such as Kubernetes.
  • A pragmatic focus on serving latency, reliability, and measurable customer impact over novel theoretical architectures.

Responsibilities

  • Build and ship core product machine learning capabilities, including send-time and frequency optimization, recommendation engines, and campaign personalization.
  • Own the end-to-end model lifecycle, including exploratory data analysis, feature engineering, distributed training, production deployment, latency monitoring, and online experimentation such as multi-armed bandits and ensemble models.
  • Build and scale data pipelines and serving architectures using Databricks, Spark, AWS, Ray, and Kubernetes.
  • Partner with Backend and Platform teams to improve feature serving and overall data architecture, and establish engineering standards across the team.
  • Mentor engineers on the team and help set the technical direction for machine learning.
  • Build, evaluate, and integrate new models that add intelligence to the core product.
  • Enhance models that optimize the send time and frequency of outgoing message campaigns.
  • Design data pipelines that make it easier to implement and test new models.
  • Work with platform engineers to enhance feature- and model-serving architecture.
  • Benchmark and improve the multi-armed bandit implementation.
  • Build tools to visualize and debug features and models.

Desired Qualifications

  • Prior work on large-scale recommendation systems.
  • Experience setting up feature stores or model observability tools.
  • Exposure to Infrastructure-as-Code tools such as Terraform or Pulumi.

About the Company

Iterable

Real-time cross-channel customer engagement platform

Iterable is a customer engagement platform that uses real-time data to power personalized marketing across channels. It enables businesses to design adaptive, one-to-one content and automate journeys, orchestrating cross-channel communications to reduce noise and boost impact. Its AI-driven features enhance message relevance and support native app and OTT communications, using enriched location data for scalable personalization and localization. The platform is offered on a subscription basis, with pricing supporting various client sizes and needs. Iterable targets marketers who want more precise, timely customer interactions and better lifecycle understanding, helping them not just survive economically but thrive with more effective, personalized campaigns.

Company size
501-1,000
Company stage
Series E
Total funding
$342.2M
Headquarters
San Francisco, CA
Founded
2013

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