Staff ML Engineer, Audio Tooling & Generative Models

Riot Games; Singapore; On-site; SGD 180,000 - 280,000; Full time

Benefits offered by this job

Full relocation support

Full health insurance for you, your_sp

Job summary

Riot Games Singapore is seeking a Staff Machine Learning Engineer, Audio, to build assistive audio tooling and empower sound designers. You will lead end-to-end ML projects in audio, collaborate with design and engineering teams, and push state-of-the-art techniques into production in a fast-paced gaming environment.

Ideal candidates have 5+ years in ML, deep audio expertise, strong Python/C/C++, and experience with PyTorch/TensorFlow/JAX.

Qualifications

• Master’s or Ph.D. in Computer Science, Statistics, Mathematics, or a related field with a focus on Machine Learning/AI.
• Audio specialization with deep expertise in audio ML, including generative audio, vocoders, text-to-speech/voice conversion, and music modeling.
• 5+ years of applying ML to real-world problems with a track record of end-to-end solutions in Audio.
• Proven ability to work on state-of-the-art approaches and ship production-ready audio ML systems.

Responsibilities

• Build assistive audio tooling to reduce repetitive steps in the sound design workflow.
• Collaborate with sound designers and engineers to deliver impactful tooling.
• Define and run evaluations for audio quality and quantify time savings.
• Keep up with audio ML developments and apply them within production constraints.

Skills

Audio ML

Deep learning

Python

C/C++

Team leadership

Communication

Mentoring

Education

Master's or Ph.D. in CS/Statistics/Mathematics with ML focus

Tools

PyTorch

TensorFlow

JAX

Job description

Riot Games Singapore is seeking a Staff Machine Learning Engineer, Audio, to build assistive audio tooling and empower sound designers. You will lead end-to-end ML projects in audio, collaborate with design and engineering teams, and push state-of-the-art techniques into production in a fast-paced gaming environment.

Ideal candidates have 5+ years in ML, deep audio expertise, strong Python/C/C++, and experience with PyTorch/TensorFlow/JAX.