ML Engineer

We're looking for a Senior Data Scientist/ML Engineer who's excited to build models that ship, not just models that impress.

The Role

This is a senior individual contributor role sitting at the intersection of data science and engineering. You'll design and deliver machine learning solutions that directly power Campaignswell's product, from revenue prediction, and probabilistic attribution to internal tooling that makes our analysts faster and smarter.

You'll work closely with Product and Analytics, and have real ownership over the ML roadmap. We're at a stage where the right person can shape how we do this, not just inherit someone else's decisions.

Responsibilities

• Design, build, and deploy ML models into production from problem framing through to monitoring and iteration.
• Develop predictive features for the Campaignswell platform (e.g. revenue forecasting, probabilistic attribution, audience segmentation, anomaly detection).
• Collaborate with Product and Engineering to define how ML capabilities are surfaced to customers.
• Build and maintain scalable ML infrastructure and pipelines in close partnership with the data engineering team.
• Establish best practices for model evaluation, versioning, and monitoring.

Requirements

• 4+ years of experience in data science or ML engineering, with a strong track record of shipping models to production.
• Proficiency in Python and the core ML stack (frameworks of gradient boosting, NN).
• Solid understanding of MLOps principles — you care about how models behave after they're deployed, not just how they perform in a notebook.
• Experience with cloud platforms (AWS) and modern data infrastructure (dbt, Snowflake, Airflow, or similar).
• Strong statistical foundations, you know when to use a simple model and when complexity is justified.