.My Sheet Music Transcriptions is at the forefront of sheet music and digital music notation services.
While we believe music is a human phenomenon, we are committed to creating solutions that not only advance the field of music technology, but also support and enhance the creative process of musicians and composers worldwide.Our mission is to leverage cutting-edge technology to enhance—not replace—human creativity, empowering musicians and artists through reliable tools that streamline the music creation process.We are excited to expand our team and are seeking a Senior AI Engineer to lead the deployment of music technology solutions.
You will work alongside our team and collaborate with the Music Technology Group (MTG) at Universitat Pompeu Fabra, one of the leading research hubs in music tech.What You'll Do: As a Senior AI Engineer, your role will focus on integrating cutting-edge technology into scalable products for music notation.
You will bridge the gap between research prototypes and real-world applications by transforming provided AI engines into robust, production-ready solutions.Key Responsibilities: Conduct research and development in music information retrieval (MIR) with a focus on symbolic music data, designing, implementing, and evaluating algorithms for analysis and generation.Develop web-based applications to showcase and deploy symbolic music technologies, integrating them into user-friendly solutions through collaboration with cross-functional teams.Stay updated on advancements in symbolic music analysis, MIR, and web technologies.Transform prototypes into scalable, user-ready products, integrating third-party AI engines and applying MLOps best practices for deployment, monitoring, and maintenance.Optimize AI algorithms to meet technical and creative product requirements, with a focus on audio signal processing, music understanding, and automatic transcription.Ensure the scalability, reliability, and performance of deployed solutions.Requirements: PhD in Music Technology, Computer Science, Electrical Engineering, or related field, with expertise in symbolic music analysis, Music Information Retrieval, and audio signal processing.Demonstrated experience in symbolic music analysis, including working with music scores, notation systems, and transcription techniques (preferred but not required).Proficiency in deploying web applications and AI prototypes to production-level products, utilizing cloud platforms (e.G., AWS, GCP) and MLOps tools (e.G., Docker, Kubernetes, MLflow).Solid background in machine learning, audio processing, and music, with fluency in English (written and spoken).Nice to Have: Knowledge of music theory, particularly related to notation and score analysis.Proficiency in machine learning and deep learning applied to symbolic music data, with experience using frameworks like PyTorch or TensorFlow.Understanding of the music industry's needs