Personalization and automated decision engineer for MarTech at MoneyLion

Gen is a global leader dedicated to powering Digital Freedom through trusted consumer brands, including Norton, Avast, and LifeLock. Our products help people live their digital lives safely, privately, and confidently. About the role Gen’s Martech organization is evolving from manually defined campaign and message-selection rules toward intelligent, learned decisioning. We’re looking for a senior/staff-level Personalization & Decisioning Engineer to become the founding engineer for this transformation. You’ll build and own the systems that decide which message or creative to deliver, to whom, and when. This includes a contextual-bandit-based message-selection platform, a content-embedding pipeline that enables new creative to generalize immediately, and the low-latency serving and feedback infrastructure that connects these capabilities to production experiences. You’ll partner with product, marketing, data science, engineering, business, and compliance stakeholders to improve relevance and outcomes while ensuring safeguards—including frequency caps, eligibility rules, customer protections, and required disclosures—remain enforced above the models. What you’ll do Design, build, and operate a production-grade contextual bandit for message and campaign selection. Own the content-embedding pipeline that supports rapid generalization to new creative without requiring a full history of prior interactions. Build low-latency online serving systems and reliable feedback loops for impressions, selections, conversions, outcomes, and model learning. Establish evaluation, experimentation, monitoring, and rollback practices for safe production operation. Translate business and compliance requirements into durable system safeguards, including frequency caps, eligibility conditions, suppression rules, and disclosures. Make pragmatic modeling and architecture choices, using the simplest approach that meets business needs and earning complexity through measurable value. Mentor engineers and help shape the technical direction and roadmap for personalization and decisioning across Martech. What you’ll bring Significant experience designing and delivering production machine-learning or decisioning systems, typically at a senior or staff level. Demonstrated experience shipping a contextual bandit, recommender system, ranking system, or comparable online decisioning capability into production. Strong software engineering fundamentals and experience building reliable, observable services, real-time inference APIs, event-driven feedback systems, and production data pipelines. Practical knowledge of experimentation and online evaluation, including metrics, bias, exploration versus exploitation, and failure modes. Experience with embeddings, representation learning, content understanding, or systems that generalize to new items. Sound judgment about model complexity, operational risk, and when a simpler solution is the right one. Ability to communicate clearly with te