Yubo
Infrastructure
SeniorMLEngineer
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior ML Engineer at Yubo. Skills: Machine Learning, MLOps, Platform Engineering. Deliver end-to-end ML use cases. Design ML models”
What You'll Achieve.
Deliver end-to-end ML use case; Audit and improve lifecycle management; Refactor and retrain legacy safety model; Build reusable ML components; Improve monitoring and observability; Contribute to ML platform evolution; Move critical ML systems toward reliable operation
Industry & Context.
Structure complex problems
2 days at office per month
What They're Looking For.
Must Have
5+ years of experience in ML / Data, Experience with large-scale datasets, Expertise in modern ML frameworks, Highly proficient in Python, Knowledge of neural networks, Practical experience with LLM-based systems, Understand ML systems end-to-end, Experience in production ML systems
Nice to Have
TensorFlow or PyTorch or JAX expertise, Product sense, Pragmatic and impact-driven, Able to explain complex ML topics clearly, Operate well under ambiguity, Able to drive technical decisions, Influence stakeholders through expertise and collaboration
What You'll Do.
Deliver end-to-end ML use cases
Balance speed with robustness
Drive improvements across ML lifecycle
Establish monitoring standards
Ensure alignment with product objectives
Ensure alignment with safety objectives
Improve reliability of production ML systems
Improve observability of production ML systems
Contribute to ML platform evolution
Establish scalable ML engineering practices
Improve self-service ML capabilities
Take ownership of legacy models
Realign legacy models
Improve legacy models
Retrain legacy models
Integrate legacy models
Contribute to best practices LLM usage
Explore advanced ML approaches
Implement advanced ML approaches
Partner with Data Engineering
Partner with Backend Platform
Partner with Product teams
Act as bridge between ML
Act as bridge between platform
Act as bridge between business
Provide technical leadership
How You'll Work.
Team & Collaboration
Cross-functional collaboration; Partner with teams; Technical leadership; Share knowledge; Raise maturity
Communication Scope
Explain complex topics
Full Job Description
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 pote
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