AI/Machine Learning Engineer, Neuro-AI
Description
Cahira Technologies – Revolutionizing Neuro-Intervention
Are you an exceptional AI/ML Engineer with a passion for transforming human capabilities and treating neurological diseases? Join Cahira Technologies, a groundbreaking neurotech startup poised to redefine personalized brain intervention. We're building the future of adaptive neuromodulation, leveraging vast neuroscientific datasets to develop intelligent systems that optimize cognitive function and precisely target disease states.
We are seeking AI/Machine Learning Engineers who will architect and implement the core AI pipelines that drive our innovative solutions. This is a unique opportunity to build the future of Neuro-AI and make a transformative impact on human health and performance.
What you'll do:
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 (e.g., learning, memory, attention).
Identify and predict pathological brain patterns associated with neurological disorders (e.g., seizure, Parkinson’s, Alzheimer’s, brain cancer, chronic pain).
Generate personalized, adaptive neuromodulation parameters for both enhancement and disease treatment.
Drive the selection of appropriate AI/ML frameworks, tools, and cloud infrastructure.
Collaborate closely with our Computational Neuroscientist to ensure scientific rigor and clinical relevance of our AI models.
Contribute to our intellectual property and scientific publications.
Required Skills & Experience:
PhD or Master's degree in Computer Science, Electrical Engineering, or a related quantitative field.
5+ years of experience in AI/Machine Learning engineering, with a strong portfolio of successfully deployed ML models.
Expertise in Deep Learning architectures, especially for time-series data (RNNs, LSTMs, Transformers, CNNs).
Proficiency in Python and leading ML frameworks (e.g., PyTorch, TensorFlow).
Demonstrated experience with multimodal data fusion and complex data preprocessing.
Solid understanding of MLOps principles for building robust and scalable ML systems.
Experience with cloud computing platforms (AWS, GCP, Azure) and their AI/ML services.
Preferred Skills & Experience:
Experience with Reinforcement Learning (RL) for control systems or optimization.
Familiarity with neuroscientific data (EEG, fMRI, LFP, spikes) and common neuroimaging/electrophysiology analysis toolboxes.
Experience with Explainable AI (XAI) techniques for medical/neuroscience applications.
Experience with Edge-AI
Experience with foundation models
Background in signal processing for biological signals.
Skills
As published by dover · 16 questions
Short answers (12)
- Current Affiliation
- Bachelors University, department and graduation date
- M.S. University, department and graduation date (if applicable)
- PhD University, department and graduation date (if applicable)
- List of your skills
- Are you currently in Boston or are willing to relocate to Boston?
- When is the earliest you can join?
- 1. months or years of experience with Deep Learning architectures for time-series data ? 2.Briefly mention time series data you have worked with 3. Add references to your published papers relevant to this skill. If you have more than 3 relevant papers, mention number of papers and provide reference to 3 most significant 1st authored publications.
- 1. months or years of experience with neuro-AI? 2. Briefly mention what you have done 3. Add reference to your published works. (Note that this skill is not required)
- 1. months or years of experience with building foundation models? 2. Briefly mention what you have done 3. add reference to your published works. (Note that this skill is not required)
- LinkedIn Profile URL
- Phone optional
Pick from a list (3)
- Are you currently located in USA? (answer only yes or no)
- Are you authorized to work for an employer in the United States? (answer only yes or no)
- Do you require work authorization or visa sponsorship for this position? (answer only yes or no)
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