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Product Manager - AI & ML

Job in Bellevue, King County, Washington, 98009, USA
Listing for: Warner Bros. Discovery
Full Time position
Listed on 2025-11-10
Job specializations:
  • IT/Tech
    AI Engineer, Data Analyst, Data Science Manager, Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 60000 - 80000 USD Yearly USD 60000.00 80000.00 YEAR
Job Description & How to Apply Below
Position: Staff Product Manager - Growth AI & ML

Overview

At Warner Bros. Discovery, we bring stories to life through cutting‑edge technology and creative talent. HBO Max, part of our global streaming brand, is one of the world’s most iconic entertainment platforms, delivering bold originals and unforgettable content across 90+ countries. We’re seeking a visionary product manager to help shape the next generation of personalized experiences.

Your New Role

We are seeking a visionary AI/ML Product Manager to lead the development of HBO Max’s Growth AI/ML platform. You will shape the end‑to‑end strategy for personalized experiences that drive subscriber acquisition, retention, and lifetime value. This role is highly cross‑functional and technically complex, requiring comfort across machine learning infrastructure, experimentation, pricing, platform limitations, and global business needs.

You will own the personalization strategy that powers key subscriber flows, collaborating closely with ML Engineers, Data Science, and Growth Product teams to turn predictive models into scalable decision‑making systems. With your deep product background, you’ll investigate, consume data, evaluate opportunities and write technical requirements for Engineering and ensure smooth implementation across product surfaces. You’ll play a key role in shaping roadmaps, informing monetization strategy, and delivering a cohesive experience across the subscriber journey.

Strategy

and Vision
  • Define and own the product strategy and roadmap for ML‑driven personalization across the subscriber lifecycle.
  • Translate HBO Max’s monetization and growth objectives into scalable, testable, and personalized experiences—such as upgrade prompts, discount offers, time‑bound sampling, re‑engagement, upsell, and retention strategies.
Execution and Delivery
  • Collaborate with Data Science and ML Engineers to design and deploy predictive models (e.g., take‑rate models, contextual bandits) that inform messaging, offer type, duration, discount level, and plan selection.
  • Operationalize model outputs into product features through configurable offer logic, eligibility criteria, and business guardrails.
  • Ensure smooth integration of ML features into existing user flows (e.g., signup, cancel, resubscribe), in partnership with PMs who own those surfaces.
Measurement and Optimization
  • Partner with Data Science, Experimentation, and Analytics teams to define KPIs, set up experiments (A/B tests, Multi‑Armed Bandits), and interpret results to assess offer effectiveness and model accuracy.
  • Iterate on models and offer strategies based on experimental results, behavioral insights, and business context.
  • Maintain an always‑on learning agenda to evolve personalization strategies over time.
Infrastructure and Enablement
  • Define product requirements for offer experiences, as well as the systems that support ML‑powered offer delivery—including feature pipelines, targeting infrastructure, and override controls.
  • Partner with Engineering and Data Platform teams to ensure infrastructure is scalable, performant, and adaptable across global markets.
  • Advocate for tools and systems that enable non‑technical teams to configure, test, and manage offers safely and effectively.
  • Integrate and leverage modern AI productivity tools (Claude, Lovable, Replit, n8n, Zapier) and protocols (MCP) to accelerate product development and experimentation.
Qualifications & Experience
  • 7+ years of product management experience in subscription, growth, monetization, or AI/ML‑driven products.
  • Proven track record of partnering with Data Science and Engineering to launch AI/ML‑powered features at scale.
  • Hands‑on experience with experimentation frameworks (A/B testing, multi‑armed bandits, holdouts), especially for lifecycle and offer optimization.
  • Ability to rapidly prototype solutions from prompt to working code using AI productivity tools (Claude, Lovable, Replit, n8n, Zapier) and familiarity with MCP protocol.
  • Experience creating and deploying AI agents to automate workflows and enhance product capabilities.
  • Strong product intuition with the ability to balance data, model performance, business goals, and user experience.
  • Comfortable working with backend systems, data…
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