Audio Inference Engineer, Model Efficiency

• Significant experience developing high-performance audio or machine learning inference systems.
• Proficiency with programming languages such as C++ and Python.
• Hands-on experience with deep learning models for audio, speech, or language applications.
• A bias for action and a strong results-oriented mindset.

It is a big plus if you also have considerable experience with:

• GPU programming, low-level system optimization, model parallelization techniques over multiple GPUs
• Have experience with duplex real-time streaming architectures.
• Internals of machine learning frameworks for audio (such as PyTorch, TensorFlow, or specialized audio libraries).
• Have experience with inference framework like vLLM, SGLang, Tensort-LLM, or custom distributed inference systems
• Sequence modeling (e.g., transformers for audio/speech) and end-to-end audio pipeline optimization

Working location:

This role can be based remotely or from one of our office locations listed on the job description - there is no minimum in-office qualification requirement. We care most about hiring exceptional people regardless of locations, though please check the location listed on the posting for guidance around the core time zone or working hours alignment expected for the role.