smule

Internship - Applied Research Scientist

Salt Lake City, Utah, United States · Intern · Internship

Sponsorship not specifiedDetected 20 days ago

PythonMachine LearningTensorFlowPyTorchData EngineeringData ScienceStatisticsElectrical EngineeringSignal ProcessingResearch

About the role

Music is much more than listening… it's about creating, sharing, discovering, participating, and connecting with people.
We strongly encourage candidates with non-traditional ML backgrounds to apply.

Develop and adapt state-of-the-art ML techniques to solve concrete product challenges in areas such as audio processing, content understanding, recommendation, and generative music, delivering measurable improvements in quality, latency, or user experience.
Design and run rigorous offline and online experiments (A/B tests, ablation studies) to validate model improvements before production deployment.
Collaborate closely with product managers, designers, and engineers to translate user needs into well-scoped research problems.
Build prototype models and proof-of-concept systems that demonstrate feasibility and inform production architecture decisions.
You will take ideas from the research frontier, or originate your own, and develop them into practical solutions that improve Smule's products, pipelines, and user experience for a community of millions.

Degree (B.S., M.S., or Ph.D.) in Computer Science, Software Engineering, Electrical Engineering, or a related technical discipline, or currently pursuing one.
Demonstrated ability to take research ideas from paper to production, with experience shipping ML-powered features or systems.
Proficiency in Python, PyTorch or TensorFlow, and standard ML infrastructure (data pipelines, model serving, monitoring).
Track record of identifying high-impact problems and delivering solutions with measurable outcomes.
The ideal candidate combines research depth with strong engineering instincts, a bias toward measurable outcomes, and genuine curiosity about how people make music.

Experience with audio, speech, music, or multimedia ML applications.
Familiarity with on-device or edge deployment constraints (model compression, quantization, latency optimization).
Published work at conferences or journals, such as KDD, RecSys, EMNLP, Interspeech, ISMIR, or similar.

If your path into applied machine learning came through audio engineering, music production, signal processing, data science, or another field, we want to hear from you.

We are seeking a Research Scientist for Smule's Applied Research team who thrives at the intersection of cutting-edge ML research and real-world product impact.

This listing is sourced directly from smule's careers page and normalized into a canonical job model.