Job Description

At Cognixion, we are building the future of human-computer 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.


Reporting to the VP of Engineering, the

Staff Scientist

is responsible for the hands-on development, validation, and translation of product-focused algorithms for Cognixion's AR-BCI platform. This role bridges cutting-edge neuroscience 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.

Scope of Responsibilities:

Internal Key Opinion Leader

Remain current on advancements in neural sensing, biosignal analytics, machine learning, and clinical applications. Partner closely with research, engineering, and product teams to identify compelling algorithmic opportunities, prototype them, validate performance, and facilitate translating successful approaches into production code. Provide detailed input to hardware and software teams regarding product requirements, sensing constraints, and clinical application needs.

Algorithm & ML Developer

Design and execute data-collection protocols to advance Cognixion's neurotechnology platform, including EEG, EMG, EOG, and multimodal biosensing. 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). Prototype and implement algorithms in Python, Java, or other mainstream languages as appropriate. Apply classical and advanced signal-processing techniques, including filtering, ICA/PCA, spectral and time-frequency methods, adaptive and spatial filtering, artifact reduction, and model-based approaches. Explore and implement machine-learning and deep-learning models for classification, regression, decoding, multimodal fusion, and real-time inference. Contribute to medical-grade codebases using best practices for reliability, version control, testing, and documentation.

Skills & Experience

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. 10+ years of industry R&D experience, ideally with direct exposure to neurotechnology or bio-signal-based medical products. Demonstrated success shipping at least one product, preferably within regulated medical, neural interface, sensing, or wearable systems. Strong publication and/or patent record showing impactful innovation. Experience translating early-stage research into commercializable, validated product features. Direct experience with biomedical signals (EEG, EMG, EOG, or other non-invasive modalities), data collection, and human-subject experimentation. Deep familiarity with algorithm development, signal processing, ML/AI workflows, and real-time system considerations. * Comfortable leading experiments, designing studies, validating results statistically, and communicating findings to multidisciplinary teams.