Machine Learning Engineering Manager - Personalization

What You'll Do

• Design, build, and improve machine learning systems that power safety across personalization surfaces such as recommendations, search, and emerging AI experiences
• Contribute to the platformization of safety systems, enabling scalable and reusable solutions across teams
• Develop and operate high-throughput, low-latency backend services powered by ML models
• Partner with Product, Trust & Safety, and Content Platform to translate safety needs into practical technical solutions
• Work on both traditional ML models and generative AI systems, including integrating third-party and in-house foundational models
• Contribute to evaluation frameworks, including labeling strategies, ground truth creation, and model validation approaches
• Collaborate with foundational model teams to embed safety into LLM-based and agent-driven experiences
• Use metrics and experimentation to continuously improve system performance, safety outcomes, and user experience

Who You Are

• Experienced in building and deploying machine learning systems in production environments
• Hands-on experience with both traditional ML approaches and newer generative AI techniques
• Worked with scalable backend systems that require reliability, low latency, and high availability
• Understand how to apply ML solutions to real-world product challenges, ideally in consumer-facing products
• Experience with model evaluation approaches such as labeling workflows, red-teaming, or ground truth data generation
• Comfortable working across disciplines, collaborating with product managers, researchers, and policy partners
• Care deeply about building safe, responsible, and inclusive user experiences
• Bring a thoughtful, metrics-driven approach to problem solving and decision-making