Applied ML Scientist: Music Tech & Audio AI

Smule

Salt Lake City (UT)

On-site

USD 110,000 - 170,000

Full time

14 days+

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Job summary

Smule is seeking a Research Scientist to join the Applied Research team. You will transform research ideas into practical ML solutions that improve Smule’s products, pipelines, and user experience for a global community of music creators.

The role blends research depth with engineering rigor, requiring experimentation, collaboration with product teams, and a track record of delivering measurable outcomes. Passion for audio/music ML is a plus.

Qualifications

  • Degree in Computer Science, Software Engineering, Electrical Engineering, or related technical discipline (or pursuing).
  • Experience shipping ML-powered features or systems.
  • Strong skills in experiment design, statistics, and iterative model development.

Responsibilities

  • Develop and adapt state-of-the-art ML techniques for product challenges in audio processing, content understanding, and music recommendations.
  • Design and run offline and online experiments (A/B tests, ablation studies) to validate models before production.
  • Collaborate with product managers, designers, and engineers to translate user needs into research problems.
  • Build prototype models and proof-of-concept systems for production decisions.
  • Publish applied research findings and share knowledge internally.

Skills

Experiment design
Statistical analysis
Iterative model development
Python
ML frameworks
Communication
Problem-solving

Education

Bachelor's/Master's/PhD in CS/SE/EE or related field

Tools

Python
PyTorch
TensorFlow

Job description

Smule is seeking a Research Scientist to join the Applied Research team. You will transform research ideas into practical ML solutions that improve Smule’s products, pipelines, and user experience for a global community of music creators.

The role blends research depth with engineering rigor, requiring experimentation, collaboration with product teams, and a track record of delivering measurable outcomes. Passion for audio/music ML is a plus.

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