Machine Learning Engineer - Data & Evaluation

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 (www.thehumeinitiative.org). You can learn more about us on our website (https://hume.ai/) and read about us inAxios and The Washington Post.

About the Role

We are looking for an experienced and motivated engineer with experience in large scale data pipelines for machine learning training and evaluation. In this role you will partner closely with researchers to collect and process essential data for training multimodal LLMs. You will create and implement evaluations, manage training data pipelines, and integrate open source packages and frameworks to accelerate training. This engineering-focused role combines data platform development with research engineering.

You may be a good fit if you

• Have expertise in the Python ecosystem and popular ML libraries and tools (e.g. PyTorch, JAX, TensorFlow).
• Are familiar with tools such as Elasticsearch, Ray, Dask, Flink, Spark.
• Enjoy translating research questions into concrete experiments backed by data and measurement.
• Have experience with web development for interactive tools that accelerate research.
• Are comfortable designing data schemas and manipulating large data sources in BigQuery, Redshift, etc.
• Excellent communication and collaboration skills.

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.