Automotive Audio Systems Engineer
Qualcomm · Hyderabad · 2+ yrs experience · Posted 2026-02-19
Tech stack: C, Python
About the role
Qualcomm India Private Limited
Engineering Group, Engineering Group > Systems Engineering
Responsibilities: - Qualcomm’s Audio Systems and R&D team is seeking a talented and highly motivated engineer specializing in the implementation of Digital Signal Processing (DSP) algorithms and Machine Learning (ML) models for next-generation in-vehicle audio experiences.
- This role involves hands-on development, integration, evaluation, and optimization of advanced audio algorithms on Snapdragon platforms, with an emphasis on ensuring robust, real-time performance in embedded automotive environments.
- Design, develop, and optimize DSP algorithms for automotive audio applications (e.g., noise reduction, echo cancellation, audio enhancement, Zonal Voice, etc.).
- Implement Machine Learning models and audio signal processing modules for deployment in embedded systems.
- Integrate audio algorithms into embedded platforms, ensuring that real-time performance and robustness requirements are met.
- Collaborate with cross-functional teams (hardware, software, systems) for algorithm integration and productization.
- Perform root cause analysis and debugging of audio system issues, proposing and implementing effective solutions.
- Stay up-to-date with the latest advancements in audio DSP, ML, and automotive compliance and standards, and contribute innovative ideas to the team.
Qualifications: - Solid understanding of Audio Signal processing
- Strong programming experience in Embedded C, real-time DSP.
- Basic understanding of Python and ML.
- Proven experience with DSP algorithm design and implementation for audio applications.
- Hands-on experience working with ACQUA, Audio Precision, or similar audio analysis and measurement tools.
- Experience with im plementing ML models and inference analysis for audio features
- Experience working in embedded and/or automotive environments is a plus.
- Excellent problem-solving and communication skills.
- Ability to work independently and in teams across functions and locations.
- Masters or PhD in Electronics and Communication, Electrical Engineering, Computer Science (with Signal Processing coursework or experience), or a related field (or equivalent work experience).
- Knowledge of automotive infotainment systems and their audio stack.
- Familiarity with noise reduction, echo cancellation, audio enhancement, Zonal Voice
- Familiarity with Qualcomm SDKs and tools.
- Keywords: Audio Processing, Signal Processing
- Echo Cancellation, Noise Suppression, Noise Reduction, Embedded DSP, Automotive Audio Audio datasets
- Machine Learning, Voice Recognition, Speech Recognition
- Zonal Voice, Beamforming
- Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 2+ years of Systems Engineering or related work experience.
- Master's degree in Engineering, Information Systems, Computer Science, or related field and 1+ year of Systems Engineering or related work experience.
- PhD in Engineering, Information Systems, Computer Science, or related field.
Qualifications
- Solid understanding of Audio Signal processing
- Strong programming experience in Embedded C, real-time DSP.
- Basic understanding of Python and ML.
- Proven experience with DSP algorithm design and implementation for audio applications.
- Hands-on experience working with ACQUA, Audio Precision, or similar audio analysis and measurement tools.
- Experience with im plementing ML models and inference analysis for audio features
- Experience working in embedded and/or automotive environments is a plus.
- Excellent problem-solving and communication skills.
- Ability to work independently and in teams across functions and locations.
- Masters or PhD in Electronics and Communication, Electrical Engineering, Computer Science (with Signal Processing coursework or experience), or a related field (or equivalent work experience).
- Knowledge of automotive infotainment systems and their audio stack.
- Familiarity with noise reduction, echo cancellation, audio enhancement, Zonal Voice
- Familiarity with Qualcomm SDKs and tools.
- Keywords: Audio Processing, Signal Processing
- Echo Cancellation, Noise Suppression, Noise Reduction, Embedded DSP, Automotive Audio Audio datasets
- Machine Learning, Voice Recognition, Speech Recognition
- Zonal Voice, Beamforming
- Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 2+ years of Systems Engineering or related work experience.
- Master's degree in Engineering, Information Systems, Computer Science, or related field and 1+ year of Systems Engineering or related work experience.
- PhD in Engineering, Information Systems, Computer Science, or related field.
Responsibilities
- Qualcomm’s Audio Systems and R&D team is seeking a talented and highly motivated engineer specializing in the implementation of Digital Signal Processing (DSP) algorithms and Machine Learning (ML) models for next-generation in-vehicle audio experiences.
- This role involves hands-on development, integration, evaluation, and optimization of advanced audio algorithms on Snapdragon platforms, with an emphasis on ensuring robust, real-time performance in embedded automotive environments.
- Design, develop, and optimize DSP algorithms for automotive audio applications (e.g., noise reduction, echo cancellation, audio enhancement, Zonal Voice, etc.).
- Implement Machine Learning models and audio signal processing modules for deployment in embedded systems.
- Integrate audio algorithms into embedded platforms, ensuring that real-time performance and robustness requirements are met.
- Collaborate with cross-functional teams (hardware, software, systems) for algorithm integration and productization.
- Perform root cause analysis and debugging of audio system issues, proposing and implementing effective solutions.
- Stay up-to-date with the latest advancements in audio DSP, ML, and automotive compliance and standards, and contribute innovative ideas to the team.