Machine Learning Engineer (Customer Success Engine)

About Us

We’ve got an incredible brand now we’re busy creating the legend behind it.  At hosting.com, we’ve set out to redefine the new standard for what web hosting should be — one that is authentically human, deeply trusted, and built on shared success.

Our aim and promise is bold : to become the world’s most trusted hosting company. If you’re eager to contribute your time and talent to something bigger that people will talk about long after your work is done hosting.com is your place.  If you want to do that work with and alongside incredible humans who care about each other, our customers and the work we do it’s at hosting.com.  If you believe the best success is always shared success, with your teammates, for your customers hosting.com is your next work home.

At hosting.com, we’re not just hosting websites. Although we do a great job of that for millions of websites.  We’re helping our customers tell their stories and connect with their people. Creating product experiences that helps them do that. Being there when they need us. And earning trust, day by day, by showing up and giving our best.

All because we care ... about each other’s success.  Our team is 750+ strong and growing, spread across the globe. We can’t do this alone.  Come join the journey. And help us build something better, together.

About the Role

We’re looking for a Machine Learning Engineer who combines data engineering excellence with applied machine learning expertise to help us build our Customer Success Engine — a system that predicts, segments, and activates customer insights in real time.

Your work will directly power how we engage with customers, reduce churn, and deliver personalized experiences across our tools and platforms. From developing ML models to automating feature pipelines, this role bridges data, engineering, and operational enablement at scale.

Requirements

What You’ll Do

Modeling & Feature Engineering

• Build and optimize customer segmentation, churn, and propensity models using modern ML frameworks.
• Design and maintain feature pipelines in Snowflake using SQL, dbt, and Snowpark.
• Develop reproducible training, evaluation, and scoring workflows with automated monitoring and version control.
• Partner closely with Analysts and business stakeholders to ensure models are aligned with customer and business logic.

Automation & Model Operations

Data Engineering & Infrastructure

What You'll Bring

Nice to Have

Benefits

Why Join Us

Ready to Build What’s Next?

If you’re excited by data that drives real-world impact — and you love turning machine learning models into operational success stories — we’d love to meet you.

📩 Apply now and help us power the next generation of intelligent customer engagement at Hosting.com.