GRAI is a social music app out of Warsaw, currently in alpha. We’re building new ways to listen and respond through music - focusing on the social, human interactions that only happen when people are connected on both ends. To make those connections truly resonant, we’re looking for a Lead Machine Learning Engineer to architect, build, and scale our recommendation and discovery engines. You’ll own the technical roadmap for our RecSys stack, transforming raw user behavior and social signals into deeply personalized, real-time experiences.
What You’ll Do
- Technical Leadership: Define the long-term technical vision and architectural roadmap for our recommendation and personalization engines.
- System Architecture: Design and oversee the implementation of scalable retrieval, ranking, and re-ranking pipelines capable of handling massive user behavior and content data.
- End-to-End Ownership: Lead the development of robust ML infrastructure, including automated data processing, feature stores, MLOps), and real-time model monitoring.
- Mentorship & Culture: Mentor and coach a talented team of ML engineers, fostering a culture of technical excellence, continuous learning, and rigorous experimentation.
- Data-Driven Strategy: Design comprehensive offline evaluation frameworks and lead complex A/B testing strategies to validate and iterate on model performance.
- Cross-Functional Collaboration: Partner closely with Product and Engineering to align ML initiatives with high-level business metrics and product goals.
What We’re Looking For
- Proven Track Record: Extensive experience designing, building, and scaling production-grade recommendation systems, search engines, or large-scale ranking models.
- Technical Mastery: Deep, foundational knowledge of machine learning, deep learning architectures, and modern information retrieval methodologies.
