Iterable

Senior Machine Learning Engineer, Nova Intelligence

Iterable
REMOTE - USPosted Discovered via AshbyMatch locked
RemoteFullTime5+ years expEngineering

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About the role

Iterable is the AI customer engagement platform, built for enterprise scale, loved by teams, and trusted by global brands like Redfin, SeatGeek, Priceline, Calm, and Box. Our platform empowers organizations to activate customer data from any source, design seamless cross-channel experiences, and optimize engagement with Nova Intelligence, the AI layer of our platform, all with enterprise-grade security and compliance. Today, nearly 1,200 brands across 50+ countries rely on Iterable to drive growth, deepen customer relationships, and deliver joyful customer experiences. Our success is powered by extraordinary people who bring our core values to life every day: Be an Owner, Growth Mindset, Run as One, and Transparency. And the market has noticed: G2 recognizes Iterable as a Leader globally, spanning the Americas, EMEA, APAC, ANZ, and Latin America, with category leadership in Personalization, Marketing Automation, Push Notifications, and Mobile Marketing, and a 4.5/5-star rating from hundreds of users. Gartner named Iterable a Challenger in the Gartner Magic Quadrant for Multichannel Marketing in both 2024 and 2025. We've also earned TrustRadius Top Rated honors in 2024 and 2025, were named a TrustRadius Buyer's Choice for 2026, and were featured in Snowflake's Modern Marketing Data Stack 2026. With a global presence that includes offices in San Francisco, Denver, London, Sydney, and Lisbon, plus remote employees worldwide, we are committed to building a diverse and inclusive workplace. We welcome candidates from all backgrounds and encourage you to apply. Learn more about our story and mission on our Culture and About Us pages. Let's shape the future of customer engagement together!

Location

US 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. One of our core values is a growth mindset, and Iterable is a company where everyone can grow. If this role excites you, please apply - we value applicants for the skills they bring beyond a job description.

What You'll Do

  • Build and ship core product ML capabilities, including send-time/frequency optimization, recommendation engines, and campaign personalization.
  • 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.

What We're Looking For

•

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.

Bonus points

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

You Might Work On

  • Building, evaluating, and integrating new models that add intelligence into our core product.
  • 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.

Recruitment Disclaimer

Please be aware that Iterable, Inc. ("Iterable") and our official professional recruiting agencies and platforms do not:

  • Send job offers from free email services like Gmail, Yahoo mail, Hotmail, etc.
  • Request money, fees, or payment of any kind from prospective candidates to apply to Iterable, for employment, or for the recruitment process (e.g. for home office supplies, or training, etc.).
  • Request or require personal documents like bank account details, tax forms, or credit card information as part of the recruitment process prior to the candidate signing an engagement letter or an employment contract with Iterable.

You may see all job vacancies on our official Iterable channels:

Iterable is not affiliated in any way to these impostors and we hereby confirm that such individuals/entities are not authorized, encouraged, or sponsored to act on behalf of Iterable. Such job opportunities are entirely fake and not valid. Therefore, please disregard any written or oral request for a job offer or an interview that you believe is or might be fraudulent or suspicious and immediately reach out to us via email at

talent-ops@iterable.com

upon receiving a suspicious job offer. Criminal and/or civil liabilities may arise from such actions, and Iterable expressly reserves the right to take legal action, including criminal action, against such individuals/entities whenever such phenomena occur. In any case, please note that under no circumstances shall Iterable and any of its affiliates be held liable or responsible for any claims, losses, damages, expenses or other inconvenience resulting from or in any way connected to the actions of these impostors. Iterable is an Equal Employment Opportunity employer that proudly pursues and hires a diverse workforce. Iterable does not make hiring or employment decisions on the basis of race, color, religion or religious belief, ethnic or national origin, nationality, sex, gender, gender-identity, sexual orientation, disability, age, military or veteran status, or any other basis protected by applicable local, state, or federal laws or prohibited by Company policy. Iterable also strives for a healthy and safe workplace and strictly prohibits harassment of any kind. Pursuant to the San Francisco Fair Chance Ordinance and other similar state laws and local ordinances, and its internal policy, Iterable will also consider for employment qualified applicants with arrest and conviction records.

Not included in the source posting: about the role, benefits.

Skills

machine-learningdatabrickssparkartificial-intelligencekubernetesdeep-learningpythonscalaterraformawsmarketing-automationsnowflake

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