Neuroscience PhD / ML Engineer
$150,000–$150,000 year
RemoteUnited States
Job Summary
Design, develop, and iterate on the inference model that quantifies emotional states from multimodal wearable sensor signals, bridging neuroscience research frameworks like active inference with production-grade ML systems. Collaborate with hardware and product teams to integrate the model into the wearable pipeline, taking ownership of performance, versioning, and deployment as the product moves toward broader release. Help define the scientific and engineering roadmap for the inference layer as the company scales. This founding-team position at a Y Combinator-backed startup requires a PhD in computational neuroscience or a related field with demonstrated experience moving models from theory to deployment.
Required Qualifications
- PhD in computational neuroscience, cognitive science, active inference, or a closely related field
- Demonstrated experience bridging neuroscience research and production machine learning systems
- Strong Python proficiency for ML model development and deployment
- US work authorization
- Comfort operating as both a researcher and an engineer in a fast-moving, small team
Desired Qualifications
- Hands-on experience with active inference or predictive coding frameworks
- Background working with wearable or physiological sensor data
Hiring someone like this?
Get your role in front of qualified candidates on Sorce.