Senior Machine Learning Engineer

Attentive® is the AI marketing platform for 1:1 personalization redefining the way brands and people connect. We’re the only marketing platform that combines powerful technology with human expertise to build authentic customer relationships. By unifying SMS, RCS, email, and push notifications, our AI-powered personalization engine delivers bespoke experiences that drive performance, revenue, and loyalty through real-time behavioral insights.

Recognized as the #1 provider in SMS Marketing by G2, Attentive partners with more than 8,000 customers across 70+ industries. Leading global brands like Crate and Barrel, Urban Outfitters, and Carter’s work with us to enable billions of interactions that power tens of billions in revenue for our customers.

With a distributed global workforce and employee hubs in New York City, San Francisco, London, and Sydney, Attentive’s team has been consistently recognized for its performance and culture. We’re proud to be included in Deloitte’s Fast 500 (four years running!), LinkedIn’s Top Startups , Forbes’ Cloud 100 (five years running!), Inc.’s Best Workplaces , and the Human Rights Campaign Foundation's Corporate Equality Index ! About the Role

Our Machine Learning Engineering team powers personalized experiences for hundreds of millions of customers across thousands of brands. As a Senior Machine Learning Engineer, you will play a critical role in building, scaling, and operating production-grade ML systems that drive real-time personalization across the Attentive platform.

You will operate with a high degree of ownership, partner closely with Product and Engineering, and help raise the technical bar across our ML systems in a fast-paced, high-impact environment.

What You’ll Accomplish

Design, build, and operate scalable machine learning systems used in real-time targeting, decisioning, personalization systems

Own ML projects end-to-end, from data exploration and modeling to deployment, monitoring, and iteration

Proactively safeguard model and system quality through testing, monitoring, validation, and alerting

Collaborate cross-functionally with product, data, and other engineering partners to translate business problems into ML solutions

Continuously improve system reliability, performance, and engineering efficiency

Contribute to technical direction and best practices across the ML engineering team

Mentor and support other engineers through code reviews, design discussions, and knowledge sharing

Thrive in a high-impact, fast-paced, late-stage startup environment