Personalization and Automated Decision Engineer for MarTech

Stack

Responsibilities

• ▹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 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 such as 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

Requirements

• ▹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 technical and non-technical stakeholders and align partners around trade-offs

Nice to have

• ▹Experience with personalization, lifecycle marketing, campaign optimization, recommender systems or customer engagement platforms
• ▹Experience designing deterministic policy layers and guardrails around machine-learning systems
• ▹Familiarity with privacy, consumer protection, compliance or regulated-product considerations in personalization
• ▹Experience setting technical direction for a new platform and mentoring engineers across teams

Soft skills

About the company

Gen is a global leader dedicated to powering Digital Freedom through trusted consumer brands including Norton, Avast and LifeLock. Its products help people live their digital lives safely, privately and confidently.