We’re looking for a visionary Head of Machine Learning to lead the design and deployment of cutting-edge AI systems across a global, high-volume interactive platform. You will define and execute the machine learning strategy across content personalization, intelligent moderation, computer vision, and natural language understanding — shaping the future of interactive digital experiences for millions of users worldwide.
This is a high-impact leadership role at the intersection of personalization, real-time AI, content intelligence, and behavioral analytics.
1. Personalization & Content Discovery
- Architect and scale personalization systems that power user discovery, drive engagement, and optimize platform monetization. Lead the development of recommendation engines for feeds, search, and session-aware carousels.
- Combine collaborative filtering, deep learning, and real-time ranking to personalize content across touchpoints.
- Continuously iterate based on user behavior signals to improve engagement and conversion metrics.
2. Content Understanding & Categorization
- Support and enhance robust computer vision and multi-modal models to automatically analyze and classify live visual content.
- Enable large-scale visual tagging, attribute extraction, and semantic categorization to support discoverability and quality assurance.
- Power platform-wide content structuring through automated metadata generation and classification pipelines.
3. Real-Time Interactivity Enhancement
- Drive innovation at the intersection of real-time communication and AI-driven interactivity.
- Develop NLP and LLM-based systems that enrich live engagement through context-aware, multilingual, and adaptive responses.
- Apply CV techniques to dynamically interpret on-screen environments and enable intelligent user interaction with live content.
4. Trust, Safety & Platform Integrity
- Own the development of machine learning systems that protect platform integrity and ensure safe user experiences.
- Build LLM- and CV-based moderation frameworks for content classification, behavioral detection, and adaptive risk scoring.
- Continue developing real-time fraud detection pipelines using graph analytics, user profiling, and anomaly detection models.
- Partner with internal compliance and operations teams to balance automation with precision and policy alignment.
5. Team Leadership & Execution
- Lead a high-performing ML organization of 15+ specialists across engineering, science, data, and infrastructure. Set strategic direction and align ML efforts with product, engineering, and trust & safety priorities.
- Drive operational excellence through agile experimentation, measurable iteration, and high system reliability.
- Oversee recruitment, performance development, and long-term capability building.
- Champion a culture of ownership, collaboration, and continuous learning.