Machine Learning Engineer for Embedded systems

Rubix is looking for a hands-on engineer to analyze raw EMG signals in Python, implement optimized algorithms in C++, and integrate them into an iOS application. You will be working closely with the iOS and WEB teams to ensure end-to-end data collection, processing, pattern detection, and visualization.

Employment type: Part-time - 20 hours per week

• Research and prototype development for biomedical signal processing
• Analysis of EMG data in Python: filtering, segmentation, feature extraction, and prototyping of ML models.
• Translating Python prototypes into efficient C++ code.
• Integration of modules into an iOS application, including collaboration on software architecture and CI/CD processes.
• Implementation or adaptation of ML frameworks for execution on embedded devices.
• Performance benchmarking: inference speed, memory usage, and power consumption, with iterative improvements.

• Proven experience in processing electromyographic (EMG) signals and artifact recognition
• Experience with prototyping in Python (NumPy, SciPy, pandas, scikit-learn, PyTorch, TensorFlow)
• At least 3 years of professional experience with modern C++ (C++11/14/17)
• Experience in packaging and optimizing ML models for on-device inference
• Familiarity with Xcode and interoperability of C++ modules with Objective-C/Swift code in iOS applications
• Strong ability to collaborate effectively in an agile, multidisciplinary environment

• Work on cutting-edge R&D projects combining bio-signals, machine learning, and mobile platforms
• Flexible working hours and remote work opportunities
• Flat organizational structure and collaborative culture
• Professional development (conferences, courses, certifications)