Job Opportunities API

WHO WE ARE Yubo is the Social Discovery app to make new friends and hang out online. By eliminating likes and follows, we empower our users to create genuine connections and show up as their true selves. We've pioneered a new way for Gen Z to socialize online, and with millions of active users, our goal is to redefine how we connect today and tomorrow. Our team is international, multicultural and deeply committed to its mission. As the leading platform to socialize online, we have a special responsibility to build a safe digital space for our community. Safety is embedded in our DNA, and our proactive approach focuses on user protection, support, and education. We also work closely with the broader technology industry to share our knowledge and NGOs create industry-leading child protection standards. Join us in this exciting journey and help us shape the future of social interactions! ABOUT THIS ROLE As Yubo continues to scale, Machine Learning is becoming a core production layer, powering critical systems across safety, recommendations, and product optimization. What makes this role unique is both the scale and diversity of our data, and the level of maturity we are aiming to reach. We process massive volumes of images, text, and real-time user interactions, across millions of users worldwide, creating a wide range of high-impact ML challenges, including: - Content moderation (image, text, behavior) - Recommendation systems and user engagement optimization - Behavioral detection and trust & safety models - Emerging use cases such as dynamic pricing and growth optimization At the same time, our current ML stack is still evolving. Legacy models are not fully integrated into pipelines, lifecycle management remains inconsistent, and our approach can sometimes resemble “develop, deploy, and forget.” As ML usage expands across the company, this creates increasing complexity and dependency on reliable, well-structured systems. There is still a huge amount of untapped potential, with many ML use cases yet to be designed, tested, and scaled, but unlocking it requires building a more robust and scalable ML operating model. We are therefore looking for a Staff ML Engineer to join our Platform Engineering team, reporting directly to Mikael (Head of Platform Engineering). YOUR RESPONSIBILITIES ML SYSTEMS & DELIVERY - Deliver end-to-end ML use cases (recommendation, safety algorithms, etc.). - Ensure production readiness, scalability, and long-term maintainability. - Balance speed of delivery with robustness and reliability . ML LIFECYCLE & RELIABILITY - Define and improve the full ML lifecycle (training, deployment, monitoring, iteration). - Establish KPIs and monitoring standards to track model performance over time. - Ensure continuous alignment with product and safety objectives . PLATFORM & STANDARDIZATION - Contribute to the “ML as a Platform” strategy (tools, workflows, reusable components). - Define scalable standards for ML development across teams. - Enable self-service ML capabilities . LEGACY & ADVANCED USE CASES - Take ownership of legacy models and realign them with current business needs. - Improve, retrain, and integrate them into modern pipelines. - Define standards for LLM usage (moderation, recommendation). - Explore and implement advanced ML approaches where relevant . CROSS-FUNCTIONAL LEADERSHIP - Partner with Data Engineering, MLOps, Backend Platform, and Product teams. - Act as a bridge between ML, platform, and business stakeholders. - Bring technical leadership and structure to ML practices across the organization. OUR TECHNICAL ENVIRONMENT / ML SCOPE - ML frameworks: PyTorch - Languages: Python (data stack) - Core topics: Neural networks, LLMs, data sampling - Use cases: Recommendation systems, safety algorithms, moderation - Ecosystem: Data Engineering, MLOps pipelines, Backend Platform WHO YOU ARE -