Staff Software Engineer - Inference Backends

Company: Hume AI

Location: Hume AI HQ

Salary: $170k - $280k per year

Type: Full-time

Posted: 2026-09-17

About this role

Hume AI is looking for a systems-oriented engineer to own the path from trained model to production inference. Join us in the heart of New York City and contribute to our endeavor to ensure that AI is guided by human values, the most pivotal challenge—and opportunity—of the 21st century.

## About Us

Hume AI is a Series B startup dedicated to building artificial intelligence that is directly optimized for human well-being. As the first company to release speech language models, we’re focused on expanding our research to encompass audio understanding models and evaluation platforms for enterprises.

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](https://www.nature.com/articles/s41562-022-01489-2), and support a non-profit, The Hume Initiative, that has released the first concrete ethical guidelines for empathic AI ([www.thehumeinitiative.org](http://www.thehumeinitiative.org)). You can learn more about us on our website ([https://hume.ai/](https://hume.ai/)) and read about us in [WIRED](https://www.wired.com/story/hume-ai-emotional-intelligence/), [Forbes](https://www.forbes.com/sites/rashishrivastava/2024/03/27/feeling-sad-excited-or-bored-this-startup-claims-its-ai-can-mostly-tell/), and [Venturebeat](https://venturebeat.com/ai/who-needs-gpt-4o-voice-mode-humes-evi-2-is-here-with-emotionally-inflected-voice-ai-and-api/).

## About the Role

As the first engineer dedicated full-time to inference backends at Hume, you will own the systems that take trained models from checkpoints to production inference: graph export, engine compilation, runtime integration, serving contracts, client libraries, artifact verification, and the performance and correctness of what runs in production.

You will work closely with research scientists, machine learning...

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