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Rubix Code

Machine Learning Engineer for Embedded systems

๐Ÿ“ŒSerbia, Serbia ๐Ÿ‡ท๐Ÿ‡ธ

โฑ๏ธŽ part-time

๐Ÿง™โ€โ™‚๏ธ mid-level

hybrid

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


Tasks

  • 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.


Requirements

  • 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


Benefits

  • 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)
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  • Employment

    โฑ๏ธŽ part-time

  • Experience

    ๐Ÿง™โ€โ™‚๏ธ mid-level

  • Working model

    hybrid

  • Skills
  • Industry
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