Hume AI is seeking a talented software engineer with experience in backend web services and ML infrastructure to advance our core mission: using the world’s most advanced technology for emotion understanding to build empathy and goal-alignment into AI. Join us in the heart of New York City, or wherever you are located, 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 an AI research lab and startup that provides the AI toolkit to measure, understand, and improve how technology affects human emotion. Our algorithms understand nuanced speech prosody, vocal bursts, facial expression, and tone of language—which, integrated into large language models, will determine how people experience the future of AI.

Our goal is to enable a future where technology draws on an understanding of human emotional expression to better serve human goals and emotional well-being. We provide API access to our models to researchers and developers building better healthcare solutions, digital assistants, communication tools, and more, who work with our AI tools to optimize their applications for users’ preferences and values. 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 ( ). You can learn more about us on our website ( ) and read about us in Axios and The Washington Post.

About the Role

We are looking for an experienced and motivated engineer with experience in backend web services and ML infrastructure to help Hume AI empower developers around the world. In this role you will help us integrate cutting edge AI models into services and toolkits for researchers and developers. You will work closely with research scientists and frontend engineers to build new capabilities into the Hume platform, and you will have the opportunity to take part in a wide range of engineering initiatives across the ML lifecycle, including model training, evaluation, and deployment at scale.

Requirements

Expertise in the Python ecosystem and popular ML libraries and tools (e.g. PyTorch, JAX, TensorFlow, XGBoost, sklearn, pandas, numpy).
Understanding of core ML concepts including model architecture, training, and evaluation.
Expertise working with storage and compute on a cloud platform (e.g. Google Cloud, AWS).
Deep understanding of modern deployment strategies utilizing cloud technologies. (e.g. blue/green, canary deployments, etc).
Experience using service deployment tooling (e.g. Kubernetes, Docker, Argo).li>
Excellent communication and collaboration skills.

Bonus

Experience writing backend services in multiple languages (e.g. Kotlin, Go, Rust, Java, C++).
Knowledge of one or several MLOps platforms for experiment tracking or model training (e.g. Sagemaker, Vertex, Weights and Biases).
Familiarity with distributed training and compute tools like Dask, Ray, and Spark.
Experience working at the intersection of machine learning research and engineering.

Application Note

Please apply only to the position that best aligns with your qualifications. If you submit multiple applications or have applied within the past 6 months, only your initial submission will be considered.

Annual Salary

$170,000—$250,000 USD

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