Staff Scientist, Neurotechnology

Job Description

<h3>Job Description</h3><p>Job Description<p>Salary: <br /><p>At Cognixion, we are building the future of humancomputer interaction through the Cognixion ONE, a regulated medical device that integrates augmented reality with advanced neural and biometric sensing. Our mission is to advance assisted reality by deploying transformative neurotechnology to the people who need it most. This wearable system reads and processes brain, eye, and body signals to enable novel control paradigms. <br />Reporting to the VP of Engineering, theStaff Scientistis responsible forthe hands-on development, validation, and translation of product-focused algorithms for CognixionsAR-BCI platform. This role bridges cutting-edgeneuroscience research with robust, production-grade implementations suitable for regulated medical deployment. The ideal candidate thrives equally in the lab and in software, is fluent in modern AI/ML toolchains, and can move seamlessly between biosensing experiments, algorithm development, strategic planning, and communicating research within and beyond the company. <br />Scope of Responsibilities: <br><br>Internal Key Opinion Leader</p><ul><li>Remain current on advancements in neural sensing, <span >biosignalanalytics,</span> machine learning, and clinical applications.</li><li>Partner closely with research, engineering, and product teams to identifycompelling algorithmic opportunities, prototype them, <span >validateperformance,</span> and <span >facilitatetranslating</span> successful approaches into production code.</li><li>Provide detailed input to hardware and software teams regardingproduct requirements, sensing constraints, and clinical application needs.</li></ul><p><br><br>Algorithm & ML Developer</p><ul><li>Design and execute data-collection protocols to advance <span >Cognixionsneurotechnology</span> platform, including EEG, EMG, EOG, and multimodal biosensing.</li><li>Analyze data using modern scientific and ML workflows: NumPy/SciPy, Pandas, MNE-Python, MATLAB, scikit-learn, PyTorch, TensorFlow, JAX, and associated visualization libraries (Matplotlib, Plotly, Seaborn).</li><li>Prototype and implement algorithms in Python, Java, or other mainstream languages as appropriate.</li><li>Apply classical and advanced signal-processing techniques, including filtering, ICA/PCA, spectral and timefrequency methods, adaptive and spatial filtering, artifact reduction, and model-based approaches.</li><li>Explore and implement machine-learning and deep-learning models for classification, regression, decoding, multimodal fusion, and real-time inference.</li><li>Contribute to medical-grade codebases using best practices for reliability, version control, testing, and documentation.</li></ul><p><br><br>Skills & Experience</p><ul><li>PhD or equivalent experience in engineering, computer science, applied mathematics, neuroscience, or related technical fields. Equivalent industrial experience may be considered; a technical assessment may be required.</li><li>10+ years of industry R&D experience, ideally with direct exposure to neurotechnology orbio-signal-based medical products.</li><li>Demonstrated success shipping at least one product, preferably within regulated medical, neural interface, sensing, or wearable systems.</li><li>Strong publication and/or patent record showing impactful innovation.</li><li>Experience translating early-stage research into commercializable, validatedproduct features.</li><li>Direct experience with biomedical signals (EEG, EMG, EOG, or other non-invasive modalities), data collection, and human-subject experimentation.</li><li>Deep familiarity with algorithm development, signal processing, ML/AI workflows, and real-time system considerations.</li><li>Comfortable leading experiments, designing studies, validatingresults statistically, and communicating findings to multidisciplinary teams.</li></ul><p></p></p></p>