Neuroscience PhD / ML Engineer

About this role

Join a Y Combinator–backed seed-stage startup as a founding Neuroscience PhD / ML Engineer to develop the core inference model for a wearable emotional-state detection device. You'll bridge computational neuroscience and production ML, owning the model from research through deployment as the company scales.

What you'll do

• Design and iterate on inference models that quantify emotional states from multimodal wearable sensor data (audio, biometric, etc.)
• Translate neuroscience research frameworks like active inference into production-grade machine learning systems
• Collaborate with hardware and product teams to integrate models into the wearable device pipeline
• Manage model performance, versioning, and deployment as the product moves toward release
• Define the scientific and engineering roadmap for the inference layer as the team grows
• Carry research work from initial concept through to real-world deployment

What they're looking for

• Computational neuroscience or cognitive science
• Active inference and predictive coding frameworks
• Production machine learning deployment
• Python for ML model development
• Multimodal sensor data processing
• Wearable or physiological signal analysis
• Model versioning and MLOps
• Research-to-engineering translation

Benefits

• Meaningful founding-team equity (up to 1–2%)
• Flexible remote or hybrid work arrangement
• Opportunity to lead core technical roadmap at seed stage
• Collaboration with hardware and product teams
• Based in London or San Francisco with location flexibility