Description

Develop and optimize algorithms for signal processing and machine learning, focusing on noise reduction for embedded systems.

Responsibilities

• Develop and implement Digital Signal Processing (DSP) algorithms using MATLAB.
• Design, train, and deploy machine learning models in Python for noise reduction and signal enhancement.
• Write C code for embedded systems and hardware/software interfaces.
• Optimize DSP and ML pipelines for efficiency, scalability, and performance.
• Conduct real-time noise reduction tasks to remove unwanted signals and enhance signal quality.

Required Skills

• 5+ years of experience in machine learning or signal processing roles.
• Deep understanding of DSP concepts, including filtering, spectral analysis, and signal transformations.
• Extensive experience using MATLAB for DSP algorithm development and analysis.
• Proficiency in Python for developing and deploying ML models and data analysis.
• Strong C programming skills for embedded systems development.
• Practical experience with noise reduction techniques such as adaptive filtering, Wiener filtering, or spectral subtraction.
• Proven ability to implement machine learning models for real-world applications.

Preferred Skills

• Experience with real-time signal processing in embedded systems.
• Familiarity with GPU-based computing or frameworks like TensorFlow or PyTorch.
• Understanding of time-series analysis and sensor data processing.

Key Skills

Education

Any Graduate