Engineer - Audio Systems Machine Learning Engineer
5 days ago
General Summary:
Qualcomms Audio Systems team is seeking a talented and highly motivated engineer specialized in the implementation of Voice AI and Audio solutions. You will work with a team to prototype, optimize, and productize state-of-the-art ML models, ensuring efficient deployment on snapdragon platforms
Responsibilities:
Develop, optimize, and deploy Voice AI and audio ML models for audio applications, with a focus on inference efficiency across NPUs, GPUs, and CPUs.
Perform model evaluation, quantization, and compression to enable fast, robust inference on embedded hardware.
Analyze and compare model architectures (such as Diffusion Models, U-Nets, Transformers, BERT, BART, etc.) for use in audio applications.
Collaborate with cross-functional R&D, systems, and integration teams for system use case verification and commercialization support.
Contribute to the design and software implementation of audio ML models in embedded C/C++ and Python.
Evaluate system performance, debug, and optimize for performance and robustness.
Participate in industry trends, benchmarking and performance analysis of various Model architecture, and bring up-to-date architectural or technical innovations to the team.
Requirements:
Strong programming skills in C/C++, Python.
Experience with audio processing and embedded solutions.
Hands-on experience working with audio framework and audio solutions on any platform
Familiarity with ML frameworks (PyTorch, TensorFlow, ONNX, etc.).
Knowledge of model quantization and compression techniques, and experience optimizing inference and deployment on embedded hardware.
Strong understanding of ML model architectures such as, CNNs, RNNs, Transformers, U-Nets, and statistical modeling techniques.
Understanding of DSP or Microcontroller architectures and frameworks
Experience developing and debugging software on embedded platforms; familiarity with software design patterns, multi-threaded programming (e.g., POSIX, PTHREADS), and fixed-point coding.
Excellent verbal and written communication skills; ability to work independently and as a team player in geographically dispersed, multidisciplinary teams.
Proven ability to work in a dynamic, multi-tasked environment quick learner, self-motivated, and results-driven.
Minimum Qualifications:
Bachelors, Masters or PhD in Computer Science, Electronics and Communication, Electrical Engineering, or a related field (or equivalent work experience).
Preferred Qualifications:
Experience working with Qualcomm AI HW accelerators (NPUs) and Qualcomm SDKs
Knowledge of Qualcomm Audio framework, platforms and tools
Minimum Qualifications:
Bachelor's degree in Engineering, Information Systems, Computer Science, or related field.
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