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Riot Games was established in 2006 by entrepreneurial gamers who believe that player-focused game development can result in great games. In 2009, Riot released its debut title League of Legends to critical and player acclaim. As the most played PC game in the world, over 100 million play every month. Players form the foundation of our community and it's for them that we continue to evolve and improve the League of Legends experience.
We're looking for humble but ambitious, razor-sharp professionals who can teach us a thing or two. We promise to return the favor. Like us, you take play seriously; you're passionate about games. We embrace those who see things differently, aren't afraid to experiment, and who have a healthy disregard for constraints.
That's where you come in.
Riot's Singapore Efficiency team builds the technology that lets our creative teams do their best work. In audio, a lot of a sound designer's day goes to repetitive editing, processing, and asset management rather than to the sound design itself, and that is the gap we want to close. You will be reporting to the Senior Manager, Machine Learning Engineer.
As a Staff Machine Learning Engineer, Audio, you'll build tools that handle the tedious and technical parts of audio production so sound designers and audio teams can focus on the craft of sound.
Responsibilities: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!
Our Perks:Job ID: 151883805
Skills:
Machine Learning, Jax, C, Tensorflow, Pytorch, Statistical Analysis, Python, Music Techniques, Generative Models, Evaluation Techniques, Audio Processing, Experimental Design
Skills:
Pytorch, RNNs, simulator-based prototyping, MLIR, TVM, CNNs, neural network architectures, ML compilers, TensorFlow Lite, ONNX Runtime, on-device inference toolchain development, Transformers, AI ML algorithms, quantization, model optimization