Senior Software Engineer - Backend & Machine Learning

Hume AI is seeking a talented senior software engineer with experience in backend services and ML infrastructure who is interested in working with our team to build state-of-the-art audio models and evaluation tools. 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. org ).

ai/ ) and read about us in WIRED , Forbes , and Venturebeat .

About The Role

We are looking for an experienced and motivated senior engineer with experience in backend services and ML infrastructure. 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 other 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 backend applications, cloud infrastructure, and the ML lifecycle, including evaluation and deployment at scale.

Requirements

g. PyTorch, JAX, TensorFlow, XGBoost, sklearn, pandas, numpy). Experience building and deploying models for inference services.

g. Kotlin, Go, Rust, Java, C++). Understanding of core ML concepts including model architecture, training, and evaluation.

Google Cloud, AWS). Excellent communication and collaboration skills. Bonus Familiarity with data engineering principles and/or building large-scale data pipelines.

Familiarity with building and deploying LLM-integrated products. Experience working at the intersection of machine learning research and engineering. Understanding of modern deployment strategies utilizing cloud technologies.

g. blue/green, canary deployments, etc). g.

Kubernetes, Helm, Docker, Argo).

Qualifications

If you submit multiple applications or have applied within the past 6 months, only your initial submission will be considered.