Lead Neural Architectures Research Engineer (Equity)

Ephapsys; San Francisco (CA); On-site; USD 180,000 - 280,000; Full time

Benefits offered by this job

Early-stage equity participation

High research autonomy

Job summary

Ephapsys in San Francisco seeks a Staff Research Engineer, Neural Architectures to advance ephaptic coupling in modern AI systems. You will work with the founder to formalize models, design experiments, and achieve measurable breakthroughs in performance, efficiency, and robustness.

This role emphasizes producing publishable research and translating findings into production-ready Ephapsys SDK components with platform integration and benchmarking.

Qualifications

• PhD in Machine Learning, AI, Applied Mathematics, Computational Neuroscience, or related field.
• Strong mathematical foundation (linear algebra, optimization, dynamical systems).
• Deep expertise in neural network theory and architecture design.
• Advanced proficiency in PyTorch or TensorFlow.
• Experience conducting reproducible research with controlled experimental design.

Responsibilities

• Leading the design and formalization of new ephaptic interaction operators in deep learning.
• Developing mathematical models describing cross-neuron interaction dynamics.
• Integrating ephaptic mechanisms into transformers, MLPs, and hybrid architectures.
• Conducting ablation studies and theoretical analysis of convergence and stability.
• Translating research into modular, production-ready SDK components.

Skills

Neural network theory

Mathematical foundations

Optimization

Dynamical systems

Research execution

Education

PhD in ML/AI/Applied Math/Computational Neuroscience

Tools

PyTorch

TensorFlow

Job description

Ephapsys in San Francisco seeks a Staff Research Engineer, Neural Architectures to advance ephaptic coupling in modern AI systems. You will work with the founder to formalize models, design experiments, and achieve measurable breakthroughs in performance, efficiency, and robustness.

This role emphasizes producing publishable research and translating findings into production-ready Ephapsys SDK components with platform integration and benchmarking.