Job description

Smule has been on a mission to bring the world together through music since 2008. Music is much more than listening… it's about creating, sharing, discovering, participating, and connecting with people. With dozens of millions of monthly active users creating over 20 million songs every day, Smule is connecting people all over the world through the joy of making music and transforming the music landscape from one of passive listening to collaborative creative expression and active engagement. About the Ro le: 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. 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. The ideal candidate combines research depth with strong engineering instincts, a bias toward measurable outcomes, and genuine curiosity about how people make music. We strongly encourage candidates with non-traditional ML backgrounds to apply. 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. What You'll Be Doing: 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. Publish applied research findings at relevant venues and contribute to internal knowledge-sharing through tech talks and documentation. Monitor deployed models for drift, fairness, and performance, implementing continuous improvement loops. What We're Looking For: 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. Strong skills in experiment design, statistical analysis, and iterative model development. Proficiency in Python, PyTorch or TensorFlow, and standard ML infrastructure (data pipelines, model serving, monitoring). Effective communicator who can translate between research concepts and product requirements. Track record of identifying high-impact problems and delivering solutions with measurable outcomes. Bonus Points For: 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. Smule is an Equal Opportunity Employer and considers all qualified applicants without regard to race, color, religion, sex, gender identity or expression, sexual orientation, national origin, ancestry, age, disability, medical condition, genetic information, marital status, military or veteran status, or any other protected characteristic under federal, state, or local law. We are committed to creating an inclusive environment for all employees and applicants. If you require a reasonable accommodation during the application or interview process, please let us know.

Requirements

Must-haves

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.
Publish applied research findings at relevant venues and contribute to internal knowledge-sharing through tech talks and documentation.
Monitor deployed models for drift, fairness, and performance, implementing continuous improvement loops.
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.
Strong skills in experiment design, statistical analysis, and iterative model development.
Proficiency in Python, PyTorch or TensorFlow, and standard ML infrastructure (data pipelines, model serving, monitoring).
Effective communicator who can translate between research concepts and product requirements.
Track record of identifying high-impact problems and delivering solutions with measurable outcomes.
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.
We are committed to creating an inclusive environment for all employees and applicants. If you require a reasonable accommodation during the application or interview process, please let us know.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

mlmachine learningpython

Platform: bamboohr
Effort: medium