Senior Machine Learning Engineer
GRAI
Senior Machine Learning Engineer
GRAI
Music AI infrastructure enabling collaborative remixes
We are building an AI-powered music platform that’s transforming how people create, explore, and experience music. Our product leverages cutting-edge AI technologies to provide personalized music recommendations and unique features tailored to every music enthusiast.
As we continue to grow, we’re looking for a Senior Machine Learning Engineer to design, build, and scale recommendation systems that deliver highly relevant, personalized experiences to our users. You will work on large-scale user interaction data, develop retrieval and ranking models, and take them from experimentation to production.
Design and implement retrieval and ranking architectures for personalized recommendations
Work with large-scale user behavior and content data to extract meaningful signals
Build end-to-end ML systems: data processing, feature engineering, training, evaluation, deployment, monitoring
Run A/B tests and offline evaluations to measure model impact and guide improvements
Collaborate with product and engineering teams to align recommendations with business goals
Continuously monitor model performance
Strong hands-on experience building recommendation systems or ranking models
Deep understanding of machine learning fundamentals and evaluation methodologies
Experience working with large-scale data (SQL, Spark, or distributed data systems)
Proficiency in Python and modern ML frameworks (PyTorch, TensorFlow)
Understanding of core ML concepts: supervised/unsupervised learning, evaluation metrics, feature engineering
Experience deploying ML models to production and maintaining them over time
Ability to balance experimentation with production reliability
Experience with real-time recommendation systems
Knowledge of search / information retrieval systems
Familiarity with feature stores, model monitoring, and ML infrastructure
Experience in media, music, or consumer-facing personalization products
Work on high-impact ML systems used by real users at scale
Ownership over meaningful technical decisions, from modeling to production
Collaborative, product-driven environment with strong engineering culture
A supportive and dynamic startup culture where your ideas and contributions truly matter
Opportunities for growth, learning, and shaping the future of our recommendation stack
GRAI builds infrastructure for participatory music experiences that let people remix licensed songs they love, not just generate from scratch. Its apps—Music with Friends (iOS) and Remix Playground (Android)—enable collaborative remixing and provide an AI music sandbox. The platform uses a taste and participation graph, a real-time audio system, and a derivatives pipeline that keeps every remix linked to the original track so royalties can be shared with rights holders. By focusing on rights-aligned remixing and linked derivatives, GRAI aims to grow consumer products and create a new monetization path for artists, labels, and creators.
Explore more opportunities at GRAI