AI / Machine Learning Engineer II

The role

You will build machine learning systems to improve customer growth, retention, personalization, pricing, and recommendations. This role focuses on applied machine learning, experimentation, and business-impact modeling to personalize customer decisions.

What you will do

• Lead applied machine learning initiatives from data preparation to production deployment and monitoring.
• Deploy and operate scalable ML solutions with workflows for inference, evaluation, and retraining.
• Design and analyze A/B tests, holdouts, and validation frameworks.
• Design and build propensity, response, uplift, recommendation, ranking, and optimization models.
• Partner with ML infrastructure, data engineering, backend engineering, product, analytics, and business teams.
• Build agentic tools, automation, and reusable modules to streamline ML workflows.

Required qualifications

• Five or more years of professional experience in applied machine learning, data science, ML engineering, applied statistics, or a related field, or equivalent demonstrated impact.
• Experience building and evaluating models using large-scale behavioral, transactional, product, marketing, or customer data.
• Experience designing experiments, defining success metrics, measuring incrementality, interpreting results, and translating findings into decisions.
• Experience partnering with engineering, product, analytics, and business teams to deploy and operate production ML systems.
• Strong Python skills.
• Hands-on experience with common ML frameworks, supervised learning, model selection, hyperparameter tuning, evaluation, and performance diagnosis.
• Strong SQL skills.
• Experience with BigQuery, Spark, or similar platforms for data collection, cleaning, preprocessing, exploration, and feature development.
• Strong statistical reasoning and practical knowledge of A/B testing, holdout design, causal measurement, incrementality, statistical significance, and business-impact analysis.
• Experience with cloud ML platforms, deployment pipelines, batch or real-time inference, CI/CD, model registries, monitoring, observability, retraining, rollback, and scalable system design.

Nice to have

• A technical degree in Computer Science, Data Science, Statistics, Mathematics, Operations Research, Economics, Engineering, or a related field is helpful.
• A Master’s or PhD in a quantitative field.
• Experience with recommender systems, uplift modeling, contextual bandits, pricing, or lifecycle personalization.

Benefits

• Flexible working options
• Time off
• Competitive pay
• Benefits
• Well-being programs

Before you apply

• Video Introduction: Submit a brief video introducing yourself, your work, and your most relevant experience.
• Technical interview: Demonstrate your applied machine learning, analytical, and engineering capabilities.
• Hiring manager interview: Meet with the hiring manager to discuss your background and fit for the role.
• Final interview: Meet with our AI leadership, including the Chief AI Officer, for a final assessment.

About the company

Gen is a global company dedicated to powering Digital Freedom through brands including Norton, Avast, LifeLock, and MoneyLion. They deliver cybersecurity, online privacy, identity protection, and financial wellness solutions to nearly 500 million users.