Experience with feature engineering and model lifecycle management
Marigold is seeking a Staff Applied ML Engineer to join their fully remote team, focusing on building and scaling machine learning capabilities to enhance customer outcomes across their marketing technology platforms. The ideal candidate will have extensive experience in applied machine learning, strong coding skills, and a collaborative mindset
Job Summary
This role involves designing and deploying predictive machine learning models to improve customer outcomes across the Campaign Monitor platform.
The company offers a remote-first culture with flexible hours, unlimited annual leave, and strong support for work-life harmony.
Candidates will partner closely with product teams and engineers to turn ambiguous product questions into concrete ML use cases with measurable business impact.
Matching Summary
Match Score: 85
Marigold is seeking a Staff Applied ML Engineer to join their fully remote team, focusing on building and scaling machine learning capabilities to enhance customer outcomes across their marketing technology platforms. The ideal candidate will have extensive experience in applied machine learning, strong coding skills, and a collaborative mindset.
Skills & Requirements
Must-have
7-8+ years building ML systems in production
Strong experience with Python and ML tooling
Experience with feature engineering and model lifecycle management
Production inference and MLOps practices
Backend systems and scalable architecture integration
Nice-to-have
Experience with growth or recommendation systems
Knowledge of LLMs or embeddings for content features
A/B testing and model performance validation
Building AI-enabled SaaS products at scale
Curiosity and drive to contribute to team capability
Key Requirements
7–8+ years of production ML system experience
Strong proficiency in Python
Experience integrating ML systems into production products at scale