AI / MIR Researcher (Audio Modeling Specialist) Job at Smule,Inc. in Salt Lake C

Smule Inc. is a leading US-based company specializing in developing innovative mobile software solutions. Smule is on a mission to bring the world together through music. Music is much more than listening—it’s about creating, sharing, discovering, participating, and connecting with people. With 50 million monthly active users creating over 20 million songs every day, Smule is transforming the music landscape from passive listening to collaborative, creative expression and active engagement.

We are seeking a talented and experienced AI / Music Information Retrieval (MIR) Researcher to join our team. The ideal candidate will have a strong background in artificial intelligence, machine learning, and audio modeling, with experience training models using large datasets of audio recordings. This role offers the opportunity to push the boundaries of audio-based AI technologies, working on groundbreaking projects that leverage deep learning techniques for sound transformation, source separation, music genre recognition, and more.

Responsibilities

• Design, implement, and optimize AI models trained on large-scale audio datasets.
• Preprocess, augment, and manage diverse datasets of audio recordings for efficient model training and evaluation.
• Experiment with deep learning architectures (e.g., CNNs, RNNs, Transformers) to enhance model performance.
• Evaluate model performance using metrics such as precision, recall, and F1-score.
• Conduct advanced research in AI/MIR to tackle tasks like source separation, singing voice conversion, sound transformation, audio event detection, and music genre classification.
• Collaborate with data scientists, audio engineers, and software developers to build scalable, AI-driven audio solutions.
• Work closely with product and design teams to integrate AI solutions into Smule’s products and services.
• Stay current with state-of-the-art research and incorporate new findings into ongoing projects.
• Monitor post-release product performance, gather user feedback, and make data-driven improvements.

Requirements

• Master’s or PhD in Computer Science, Electrical Engineering, Music Technology, or a related field.
• Proven experience in AI model training focused on audio processing and Music Information Retrieval (MIR).
• Proficiency in machine learning frameworks such as TensorFlow or PyTorch, with hands-on expertise in CNNs, RNNs, and Transformers.
• Familiarity with cloud computing platforms like GCP or AWS for large-scale model training.
• Hands-on experience with large-scale audio datasets, including creation, labeling, and augmentation.
• Strong understanding of digital signal processing (DSP) and its application to audio modeling.
• Experience with A/B testing for evaluating feature and design effectiveness.
• Strong analytical and problem-solving skills with a data-driven approach to decision-making.
• Proficient in Python, with experience using numeric and audio libraries (e.g., NumPy, librosa, TorchAudio) being a plus.

Benefits

• Medical, dental, and vision insurance
• 401(k) Retirement Plan
• Stock Options Plan
• Professional development opportunities
• Life, AD&D, Short-Term and Long-Term Disability coverage
• Flexible paid time off
• Parental leave
• Work-from-home stipends

Our beautiful and welcoming offices are available for meetings or focused work, whether you are traveling through or living nearby. Our U.S. offices are located in San Francisco, CA, and Salt Lake City, UT. We love seeing each other in person, so be prepared to travel for occasional in-person meetings (we cover travel costs, of course!).

Smule is an Equal Opportunity Employer
We celebrate diversity and are committed to creating an inclusive environment for all employees. We welcome applicants from all backgrounds and experiences, and we evaluate all qualified candidates without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other legally protected status. If you need assistance or an accommodation during the application process, please contact us

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