Base Salary
$180k - $350k/yr
Responsibilities
- Develop software systems for distributed model training and inference.
- Benchmark and analyze performance of speech-language models.
- Manage large-scale data collection, storage, and preprocessing.
- Contribute to solving complex AI research problems.
Requirements
- Expertise in the Python ecosystem and popular ML libraries like PyTorch.
- Experience writing robust and maintainable production-ready code.
- Ability to iterate quickly on new and uncertain research directions.
- At least 2 years of experience with large-scale datasets in text, audio, image, or video.
About Hume AI
Built from a decade of voice and emotion research. To build emotionally intelligent voice AI, we first had to define what “good” sounds like – not just acoustically, but perceptually and in real human conversations. That led us to build the research infrastructure behind expressive, trustworthy voice AI: scientifically grounded datasets, speech models, evaluation frameworks, and human preference pipelines. Today, we make that infrastructure available to frontier labs and AI-native companies building the next generation of voice. Whether you’re building foundation models, fine-tuning voice agents, or evaluating production systems, Hume provides the tools to measure, improve, and align voice AI the way people actually experience them.