This role focuses on applying cutting-edge ML technologies to real-world marketing problems by combining them with omnichannel customer data
Job Summary
This role focuses on applying cutting-edge ML technologies to real-world marketing problems by combining them with omnichannel customer data.
You will help bridge the gap between research and production by building and optimizing scalable, high-performance ML infrastructure — including data pipelines, dashboards, and monitoring systems.
Collaborate closely with ML scientists to turn research outputs into user-facing product features and partner with engineers, PMs, and other cross-functional teams to deliver high-quality AI products.
Matching Summary
This role focuses on applying cutting-edge ML technologies to real-world marketing problems by combining them with omnichannel customer data.
Skills & Requirements
Must-have
ML job execution frameworks
Kubernetes orchestration
Spark batch pipelines
PostgreSQL data infrastructure
Prometheus and Grafana monitoring
LLM-powered tools
Nice-to-have
MarTech domain experience
Kubeflow, MLflow familiarity
Distributed computing frameworks
Cloud-native ecosystems
Key Requirements
3+ years ML platform engineering, MLOps, or data infrastructure
Bachelor's degree in CS, Engineering, or related
Proficiency in Python, Java, or Go
Cross-functional collaboration and project leadership