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Hume AI

Senior/Staff AI Research Engineer

Department
Research
Job Type / Location
hybrid
Experience Required
2+ years
Posted On

About Us

Hume AI is a Series B startup dedicated to building artificial intelligence that is directly optimized for human well-being. We’re gearing up to launch the next generation of Octave and EVI, our foundational speech-language models for voice generation and powering real-time empathic AI assistants for any application.

Our models understand and generate subtle tones of voice, word emphasis, and more and the reactions of users. They are rated higher than models by OpenAI and others on empathy, expressiveness, naturalness, and speed, instantly speak with 100K+ unique voices and styles, stream language, emotion, and reasoning – all at once, and are fast enough to feel truly conversational (<300ms latency). Try them at hume.ai.

Our goal is to enable a future in which technology draws on an understanding of human emotional expression to better serve human goals. As part of our mission, we also conduct groundbreaking scientific research, publish in leading scientific journals like Nature, and support a non-profit, The Hume Initiative, that has released the first concrete ethical guidelines for empathic AI (www.thehumeinitiative.org). You can learn more about us on our website (https://hume.ai/) and read about us in WIRED, Forbes, and Venturebeat.

About the Role

We are looking for talented researchers and engineers. In this role, you will build out software systems that support distributed model training, inference, and benchmarking as well as massive-scale data collection, storage, preprocessing, and analysis. You will be working to solve some of today’s most exciting AI research problems at industry scale.

Requirements

  • Expertise in the Python ecosystem and popular ML libraries and tools (e.g. PyTorch)
  • Experience writing robust and maintainable production-ready code
  • Comfort iterating quickly on new and uncertain research directions
  • 2+ years of experience training and/or fine-tuning transformer models with large-scale datasets of text, audio, image, and/or video data

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