Responsibilities:

• Algorithm Development: Design, develop, and optimize algorithms for acoustic signal processing using machine learning techniques. Focus on enhancing the performance and accuracy of acoustic models.
• Machine Learning Implementation: Apply advanced machine learning methods, including deep learning, to process and analyze acoustic signals. Develop and train models to recognize patterns and extract meaningful information from acoustic data.
• Signal Processing: Perform advanced signal processing tasks, including filtering, feature extraction, and noise reduction, to improve the quality and reliability of acoustic signals.
• Data Analysis: Analyze large datasets of acoustic signals to identify trends, patterns, and anomalies. Use statistical and machine learning tools to interpret and validate findings.
• Research and Innovation: Stay current with the latest research and developments in the fields of machine learning and acoustic signal processing. Identify opportunities for innovation and contribute to the advancement of our technology.
• Prototyping and Testing: Develop prototypes and conduct experiments to test and validate new algorithms and models. Evaluate performance against established benchmarks and iterate to improve results.
• Collaboration: Work closely with cross-functional teams, including software engineers, hardware engineers, and product managers, to integrate acoustic signal processing solutions into products and systems.
• Documentation and Reporting: Document algorithms, models, and experimental results. Prepare technical reports and presentations to communicate findings and progress to stakeholders.
• Problem Solving: Troubleshoot and resolve technical issues related to acoustic signal processing and machine learning. Implement solutions to overcome challenges and improve system performance.