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Interhuman AI is building the next generation of social intelligence infrastructure—multimodal AI systems that understand not just what humans say, but how they say it. We're developing models that interpret behavioral signals like hesitation, engagement, confusion, and interest across voice, facial expressions, body language, and natural language - in real time. We are looking for a Student Researcher to join our AI engineering team. This is not a typical 'support' role; it is an invitation to apply the latest research in multimodal evaluation and data synthesis to a production-scale infrastructure. You will work on the practical foundations that allow our models to move from 'experimental' to 'state-of-the-art' every single week.
Job Responsibility:
Own a scoped project that upgrades how we collect, validate, or evaluate complex behavioral-signal data, directly impacting model performance
Create high-signal benchmarks to track improvements on the most challenging 'long-tail' machine learning cases in social interaction
Improve consistency and auditability across our pipeline so that our research results are trustworthy, repeatable, and scalable
Contribute to the internal ecosystem of scripts and utilities that accelerate our experiment cycles, result comparison, and artifact organization
Requirements:
Currently enrolled in a PhD program in Computer Science, Machine Learning, Data Science, or a related quantitative field (e.g., Physics, Mathematics, Statistics)
Strong proficiency in Python and experience with modern ML frameworks (PyTorch, JAX, or TensorFlow)
Deep familiarity with the current LLM/Multimodal research landscape (e.g., CLIP, Audio-LMs, Video-Language models)
Comfortable figuring things out independently and don't need constant direction
Can explain technical concepts clearly in writing and speech
Good at prioritizing and balancing multiple tasks, and flexible when changes occur
What we offer:
Highly flexible 15-hour work week designed to complement your academic schedule
Join a high-intensity, venture-backed startup environment
Paid role with direct influence on the technical direction of a pioneering social intelligence platform