General Summary:
We are seeking a highly skilled Machine Learning Engineer to join Qualcomm Multimedia Audio Systems and R&D group. The successful candidate will utilize existing trained machine learning models for a variety of audio and voice technologies, including speech enhancement, acoustic echo cancellation, noise suppression, handsfree voice calls, zonal voice calls, voice control by voice commands, keyword spotting, audio context/scene detection, source separation, and fully supervised speaker diarization. The role involves quantizing these models as needed and implementing them on Qualcomm SoCs for optimized on-device inference. We are looking for a candidate who is passionate about pushing the boundaries of audio and voice technology through innovative machine learning solutions.
Responsibilities:
The candidate will be expected to work with a team of engineers to prototype and productize Voice AI Models for Automotive
Develop, Train, and Optimize Voice AI models for efficient offload to NPU, GPU and CPU
Perform Model evaluation and performance analysis for different architectures and multiple open-source models
Work closely with other R&D and Systems team for system integration, use case validation and commercialization support
Utilize trained machine learning models for speech enhancement, acoustic echo cancellation, and noise suppression.
Develop and implement solutions for handsfree voice calls, zonal voice calls, and voice control by voice commands.
Work on keyword spotting and audio context/scene detection.
Perform source separation and fully supervised speaker diarization.
Quantize models where necessary and implement them on Qualcomm SoCs for optimized on-device inference.
Requirements:
Strong programming skills in C/C++, Python, Matlab
Experience working on Audio Signal processing algorithms and solutions
Experience working on Audio, Speech enhancement DNN models for Noise Suppression, Echo Cancellation
Basic knowledge in advanced adaptive signal processing techniques, multi-rate signal processing, adaptive beamforming, and distributed microphone-based signal processing for tracking and speech enhancement.
Familiarity with audio/voice signals and the ability to analyze them using tools like audition.
Knowledge of any ML frameworks pytorch, tensorflow, ONNX..
Familiarity with recent trends in machine learning (diffusion models, U-Nets, Transformer, BERT, BART, etc.) and traditional statistical modeling/feature extraction techniques
Knowledge of Model quantization and compression techniques
Expertise in developing and debugging software on embedded platforms
Knowledge of software design patterns and multi-threaded programming, Eg POSIX or PTHREADS
Knowledge of computer architecture, operating systems, data structures, and basic algorithms
Knowledge of fixed-point coding
Experience working on any AI HW accelerator NPU or GPU is a plus
Experience working on any DSP architecture and framework is a plus
Educational Qualification:
Bachelor's/Master’s/PhD degree in Engineering, Electronics and communication, Computer Science or related filed.
2+ years of Audio Systems engineering or Audio Signal Processing modules or ML Model development or related work experience.
Minimum Qualifications:
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