Principal Product Manager – Personalization

Overview

Yahoo serves as a trusted guide for hundreds of millions of people globally, helping them achieve their goals online through our portfolio of iconic products. For advertisers, Yahoo Advertising offers omnichannel solutions and powerful data to engage with our brands and deliver results.

Yahoo is a global media and tech company that connects people to their passions. We reach nearly 900M people around the world, bringing them closer to what they love—from finance and sports to shopping, gaming, and news—with the trusted products, content, and tech that fuel their day. For partners, we provide a full-stack platform for businesses to amplify growth and drive more meaningful connections across advertising, search, and media.

Yahoo Mail is the ultimate consumer inbox with hundreds of millions of users. It’s the best way to access your email and stay organized from a computer, phone or tablet. With its beautiful design and lightning fast speed, Yahoo Mail is embarking on the mission to create the best consumer-focused platform for running the "business of life".

• The Mail Intelligence team is seeking a visionary and deeply technical Principal Product Manager - Personalization to architect and drive the next generation of AI-powered personalization capabilities in Yahoo Mail. This role will be at the helm of designing a best-in-class recommendation engine that deeply understands user intent, context, and identity—delivering intelligent, dynamic, and personally meaningful experiences that evolve with each user over time.
• You ll lead the end-to-end strategy and execution for personalization across Mail—partnering closely with research scientists, ML engineers, data scientists, and experience teams. Your work will power real-time, multi-surface recommendations and unlock new engagement & business opportunities across Yahoo Mail s consumer products.

• Own the personalization product strategy for Yahoo Mail, aligning with Mail Intelligence s technical vision and business impact goals.
• Drive the definition of a multi-layered personalization stack—identity, embeddings, retrieval, ranking—partnering with engineering, architecture, and research to build world-class recommendation systems that unlock user value while optimizing for performance and cost.
• Lead the development of privacy-aware, context-rich systems that adapt to user intent, language, device, and lifecycle.
• Define experimentation and evaluation frameworks, including A/B testing, model performance, and relevance metrics.
• Partner with product managers driving experience and growth, as well as design and UXR teams, to integrate personalization seamlessly into user-facing flows.
• Define and track KPIs around personalization lift, relevance, engagement, and downstream impact.
• Champion a culture of personalization excellence, keeping Yahoo Mail at the forefront of innovation and research.

• 8+ years of Product Management experience in AI/ML-heavy domains—recommendation systems, personalization platforms, or search/ranking.
• Demonstrated success building and scaling real-time personalization engines or recommendation systems used by millions of users.
• Strong understanding of personalization techniques: collaborative filtering, content-based filtering, hybrid models, deep learning-based approaches.
• Hands-on experience with ML lifecycle: data acquisition, feature engineering, offline training, online inference, experimentation & evaluation.
• Exceptional communication skills with the ability to synthesize technical detail and strategic vision across varied audiences.
• Passionate about user experience, with a sharp product sense and empathy for consumer needs.
• Proven ability to align research, engineering, and cross-functional teams toward bold and measurable goals.

• Well grounded in statistics and user intent modeling.
• Familiarity with privacy-preserving personalization methods (e.g., on-device inference, federated learning, differential privacy).
• Experience scaling personalization for international and multilingual user bases.
• Exposure to real-time recommendation infrastructure and large-scale embedding…