Manager,

Job Description

Responsibilities

• Contribute towards the long-term vision for building 10-star, personalized community support, building a platform where our AI understands each guest and host the way their best human advocate would, and responds accordingly.
• Partner with data science, ML, and operations to identify new high-signal personalization signals to serve user needs
• Own the product roadmap across ML models, signals, schemas, and prompt optimization to ensure the right information reaches the model in the most effective form.
• Drive personalization experiment design and measurement: define KPIs (self-solve rate, personalization coverage, citation accuracy), lead experiment design, and translate results into clear product decisions.
• Collaborate with ML engineers to shape requirements for accuracy, latency, and scalability improvements.
• Scale personalization infrastructure across AI surfaces, ensuring the platform is extensible enough to serve each modality’s unique needs.
• Build a framework for continuous improvement: define how the team identifies personalization failures, prioritizes fixes, and systematically closes the gap between AI and human agent performance.
• Collaborate across engineering, ML, design, data science, and policy to build consensus on prioritization, drive cross-functional alignment, and ship with rigor from concept to production.

Your Expertise:

• 9+ years of industry experience with a BS/Masters OR 6+ years with a PhD, with deep expertise in AI/ML-powered platforms at consumer scale
• Strong working knowledge of personalization systems, contextual data retrieval, and LLM architectures – you can engage credibly with ML engineers on topics like RAG, retrieval optimization, and context engineering tradeoffs
• Track record of building and shipping foundational platform products that power multiple downstream experiences and surfaces
• Experience designing and interpreting A/B experiments and online experiment frameworks; ability to own end-to-end metrics strategy for complex AI systems
• Strong capacity to synthesize ambiguous signals into clear, prioritized product decisions
• Proven cross-functional leadership: able to align ML, engineering, data science, design, and operations teams around a shared vision
• Experience shipping consumer-facing AI products with personalization at the core
• Sharp product intuition for when AI automation should give way to human judgment, and how to design systems that make that transition seamless
• Ability to work at multiple levels of abstraction – from the architecture of a retrieval system to the experience of a guest trying to resolve a cancellation dispute

Are you interested in this position?
Apply by clicking on the “Apply Now” button below!
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