Engineer - Audio Systems Machine Learning Engineer

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: