AI/Machine Learning Engineer, Neuro-AI
On-site · Boston, Massachusetts, United States
Job Summary
Design, develop, and deploy scalable ML pipelines for ingesting, cleaning, and processing diverse multimodal neuroscience data (EEG, fMRI, LFP, single-spike, behavioral, clinical, blood test data). Lead the research, development, and training of advanced AI models (Deep Learning, Reinforcement Learning) to predict optimal brain states for cognitive enhancement and identify/predict pathological brain patterns, generating personalized, adaptive neuromodulation parameters. Drive the selection of AI/ML frameworks, tools, and cloud infrastructure. Collaborate with a Computational Neuroscientist to ensure scientific rigor and clinical relevance; contribute to IP and publications.
Required Qualifications
- PhD or Master's degree in Computer Science, Electrical Engineering, or a related quantitative field
- 5+ years of experience in AI/Machine Learning engineering
- Expertise in Deep Learning architectures for time-series data (RNNs, LSTMs, Transformers, CNNs)
- Proficiency in Python and ML frameworks (PyTorch, TensorFlow)
- Experience with multimodal data fusion and complex data preprocessing
- Solid understanding of MLOps principles
- Experience with cloud computing platforms (AWS, GCP, Azure) and their AI/ML services
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