Job Title: ML Research Scientist
Location: Preferred: Austin, TX ; Acceptable: Remote
Employment Type: Full-Time
Experience Level: Entry-Level (1–3 years)
About Phantom Neuro
At Phantom Neuro, we’re restoring natural movement by bridging the gap between the human nervous system and advanced robotics. Our technology decodes the language of muscle and nerve signals to enable intuitive, lifelike control of prosthetic limbs. We’re seeking a machine learning research scientist who shares our vision of giving people back not just motion, but agency. In this role, you’ll design, build, and optimize machine learning models that run in real time on embedded systems—turning EMG signals into seamless, intentional hand movement.
Job Responsibilities
- Develop and refine machine learning models to decode hand movements from EMG signals for real-time control of robotic prosthetics
- Design and conduct experiments to assess real-world efficacy of models with patients
- Review and apply state-of-the-art methods from machine learning, signal processing, and neuroscience research literature
- Build and maintain real-time data processing and analysis pipelines in Python
- Prototype and evaluate UX features for assessing model quality and improving user control experience
- Identify and build product features that meaningfully change a user’s ability to perform activities of daily living
- Translate algorithms into efficient C/C++ implementations optimized for embedded systems
Required qualifications
- Master’s degree in computer science, electrical engineering, biomedical engineering, or related field (or equivalent experience)
- Strong foundation in statistics, signal processing, and machine learning
- Proficiency in Python and familiarity with modern ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn)
- Solid understanding of software engineering principles, including testing, version control, and code optimization
Preferred qualifications
- Published research in machine learning, neuroscience, or biomedical engineering
- Demonstrated ability to design, build, and deploy machine learning models in real-world products
- Experience with embedded and/or real-time systems development
- Proficiency in C/C++ for performance-critical applications
- Prior experience working with biosignals (e.g., EMG, EEG, neural data).
