Staff Machine Learning Engineer, Audio - Singapore Efficiency Team
On-siteCentral, Louisiana, United States
Central, Louisiana, United StatesOn-siteFull TimeSenior LevelDoctorate Or Professional DegreeGamingLarge
Full TimeSenior LevelDoctorate Or Professional DegreeLargeGaming
Job Summary
Build assistive audio tooling using audio processing, voice/speech, and music techniques to remove repetitive steps from the sound designer's workflow. Partner with sound designers and audio engineers to target costly authoring and editing work, shipping tools that shorten it. Define and run evaluations for audio quality while quantifying time returned to audio teams. Follow developments in audio and speech ML, judging what holds up under production constraints. This role focuses on enabling the Singapore Efficiency Team to let creative teams focus on the craft of sound.
Required Qualifications
- Master's or Ph.D. degree in Computer Science, Statistics, Mathematics, or a related field, with a focus on Machine Learning, Data Science, or Artificial Intelligence
- Audio specialization: Deep, proven expertise in audio ML, covering generative audio, neural vocoders, text-to-speech/voice conversion, music modeling, and audio representation learning
- At least 5 years of experience applying Machine Learning to real-world problems, with a demonstrated record of delivering impactful, end-to-end ML solutions in Audio in a fast-paced environment
- Evidence of working on state-of-the-art approaches, demonstrated through peer-reviewed publications (e.g. ICASSP, INTERSPEECH, ISMIR, NeurIPS, ICML, ICLR) and/or shipped projects, open-source contributions, or production systems in Audio that pushed the technical frontier
- Proficiency in programming languages such as Python, C, C++, or C#, and strong hands-on experience with frameworks such as PyTorch, TensorFlow, or JAX
- Strong understanding of statistical analysis, experimental design, and evaluation techniques
- Deep, hands-on experience with Generative Models, including audio diffusion and flow matching models, VAEs, and autoregressive/transformer models for waveform or spectrogram modeling, applied to building artist-assistive tools and accelerating technical steps in the audio pipeline
- Excellent communication skills, with the ability to effectively communicate complex technical concepts to non-technical stakeholders
Desired Qualifications
- Leadership experience, including mentoring junior team members and interns and driving cross-functional collaboration, is highly desirable
- Experience working in the gaming industry or a related field is a plus
- For this role, you'll find success through craft expertise, a collaborative spirit, and decision-making that prioritizes the delight of players. We will be looking at your past studies, experience, and your personal relationship with games. If you embody player empathy and care about players' experiences, this could be your role!
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