Fractional ML Lead for EEG Time-Series Health Tech

Theta Neurotech; Chicago (IL); Hybrid; USD 83,000 - 193,000; Part time

Job summary

Theta Neurotech is seeking a Fractional Machine Learning Lead to guide the design and optimization of ML models powering its seizure-prediction system. This part-time hybrid role in Chicago combines technical leadership with collaboration across product and clinical teams.

You will define architectures, implement experiments, and mentor colleagues while advancing robust, real-time EEG analytics in a regulated healthcare environment.

Qualifications

• Strong CS foundation with data structures, algorithms, and software engineering principles.
• Hands-on ML/DL experience with production or research deployments.
• Statistics expertise for experimental design and model evaluation on noisy biosignals.
• Experience designing real-time inference algorithms, preferably in signal processing or biomedical apps.
• Proficiency in Python and ML frameworks (PyTorch, TensorFlow).
• Experience with EEG/time-series data and knowledge of healthcare environments is a plus.
• Excellent communication to document decisions clearly; MS/PhD or equivalent.

Responsibilities

• Define model architectures for seizure prediction.
• Implement and evaluate ML/DL algorithms on EEG data.
• Collaborate with product and clinical partners.
• Establish data preprocessing and feature engineering practices.
• Mentor team members and contribute to roadmaps.

Skills

CS fundamentals

ML/DL experience

Statistics

Time-series data

Python

PyTorch

TensorFlow

Communication

Education

MS/PhD in CS/EE/DS

Tools

Python

SciPy

NumPy

Job description

Theta Neurotech is seeking a Fractional Machine Learning Lead to guide the design and optimization of ML models powering its seizure-prediction system. This part-time hybrid role in Chicago combines technical leadership with collaboration across product and clinical teams.

You will define architectures, implement experiments, and mentor colleagues while advancing robust, real-time EEG analytics in a regulated healthcare environment.