Momentum Staffing Group LLC - Machine Learning Engineer

AI Engineer is needed in Evanston, United States.

Client: Momentum Staffing Group LLC

Location: Evanston, IL

Contract: undefined

Job Description

An early-stage medical device company is developing a wearable biosignal platform with real-time predictive capabilities, targeting a significant unmet clinical need. This technology aims to enable preventative intervention and greater patient independence for individuals living with treatment-resistant neurological conditions. This position is a founding-team role, offering meaningful technical ownership and the opportunity to directly influence both product and company direction.

Responsibilities

• Design, develop, and validate machine learning models for real-time biosignal processing and event prediction.
• Own the full ML pipeline — from raw signal acquisition and feature engineering through model training, evaluation, and on-device deployment.
• Collaborate closely with hardware, firmware, and clinical teams to ensure signal integrity and system performance.
• Contribute to regulatory documentation and ensure development practices align with relevant medical device standards.
• Drive architectural decisions and help establish engineering best practices as the team scales.

Requirements

• Strong foundation in signal processing, time-series analysis, and applied ML — ideally with physiological or biosignal data (EEG, ECG, EMG, etc.).
• Proficiency in Python and relevant ML frameworks (PyTorch, TensorFlow, scikit-learn).
• Experience with embedded or resource-constrained ML deployment is a strong plus.
• Familiarity with medical device development workflows (FDA, IEC 62304, or similar) is a plus.
• Excellent problem-solving skills and comfort working in ambiguous, fast-moving environments.
• Master’s or PhD in Computer Science, Electrical Engineering, Biomedical Engineering, or a related field preferred.

Additional Information

This role offers the opportunity to be part of a pioneering team addressing critical healthcare needs and will play a vital role in shaping the future of predictive medical technology.