Research Engineer

Hume AI is looking for a Research Engineer to advance speech-language and audio models through hands-on model development, large-scale training, and rigorous evaluation. Contribute to our endeavor to ensure that AI is guided by human values, the most pivotal challenge (and opportunity) of the 21st century.

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, 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.

As a Research Engineer, you will work with our research team to develop audio models and the tools used to study and improve them. You will turn open questions into experiments, train and refine models, and build the software that supports distributed training, inference, and benchmarking. Your work will connect model development with the data and evaluation systems needed to test ideas at scale.

Your work will span models developed in-house at Hume and models developed by our customers. You will collaborate directly with customer research and technical teams to understand their objectives, design research programs, and carry out model training, validation, evaluation, and continued development. Findings from these projects will inform new experiments and improvements to the models and methods we build.

This is a hands-on individual contributor role for someone who enjoys both open-ended investigation and building the code that makes research reproducible and useful. You will own technical work from an initial research question through experiments, analysis, and validated model improvements.

• Investigate research questions in speech-language, audio, and multimodal machine learning, and design experiments to test hypotheses about model behavior and capabilities.
• Train, fine-tune, validate, and further develop models built in-house at Hume and models developed by our customers.
• Build reliable software for distributed model training, inference, and benchmarking, making experiments reproducible and results comparable.
• Develop data workflows for collecting, storing, preprocessing, and analyzing large-scale datasets used in model training and evaluation.
• Design evaluation protocols and benchmarks that measure model quality, generalization, robustness, and progress against research objectives.
• Analyze datasets, model outputs, and failure cases; compare training approaches and use the evidence to guide the next round of model development.
• Collaborate with customer research and technical teams to define research questions, understand their models and data, and carry out training, validation, evaluation, and further development.
• Document experimental designs, results, limitations, and technical decisions so Hume colleagues and customer research teams can reproduce and build on the work.

• At least two years of experience contributing to model training or fine-tuning with large-scale text, audio, image, or video datasets, with relevant depth in speech, audio, or multimodal machine learning.
• Strong Python and PyTorch skills, including the…