Qualcomm India Private Limited
Engineering Group, Engineering Group > Systems Engineering
General Summary:
Qualcomm’s Audio Systems team is seeking a highly motivated engineer to develop, optimize, and deploy state-of-the-art audio ML models. This role focuses on bringing ML models from research to production by enabling efficient real-time inference on snapdragon NPUs under strict latency, memory, and power constraints. The role requires strong expertise in audio ML, embedded deployment, and model optimization and quantization.
• Develop, optimize, and deploy audio ML models across CPUs, GPUs, and NPUs.
• Perform model evaluation, quantization, compression, and optimization for embedded deployment.
• Integrate ML models into real-time audio pipelines such as ECNS and speech enhancement.
• Analyze and benchmark model architectures including CNNs, RNNs, Transformers, U-Nets, diffusion and sequence models.
• Optimize inference for low latency, power efficiency, and memory footprint.
• Profile and debug model performance on embedded hardware platforms.
• Collaborate with ML, DSP, and systems teams to balance accuracy vs efficiency trade-offs.
• Support end-to-end deployment, validation, and productization of models.
• Strong programming skills in C/C++ and Python.
• 3 + years of experience in ML model development, deployment, or embedded systems.
• Hands-on experience with model quantization and optimization.
• Strong understanding of real-time system constraints (latency, memory, power).
• Experience with embedded systems, DSP or AI accelerators.
• Familiarity with ML frameworks such as PyTorch, TensorFlow, ONNX.
• Experience with audio/speech ML models (speech enhancement, denoising, ECNS).
• Experience with DSP + ML hybrid systems.
• Knowledge of Qualcomm AI stack including QNN and Snapdragon platforms.
• Experience with model optimization techniques such as pruning, compression, and quantization-aware training.
• Strong understanding of audio processing pipelines and system-level integration.
• Experience with multi-threading, embedded software design, and real-time debugging on any embedded platform
Bachelor’s, Master’s or PhD in Electrical Engineering, Computer Science, Electronics and Communication, or related field.
Audio ML, Voice AI, Embedded ML, Quantization, INT8, ONNX, PyTorch, QNN, ECNS, Speech Enhancement, Model Optimization, DSP, Inference Optimization
Minimum Qualifications:
- Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 2+ years of Systems Engineering or related work experience.
OR
Master's degree in Engineering, Information Systems, Computer Science, or related field and 1+ year of Systems Engineering or related work experience.
OR
PhD in Engineering, Information Systems, Computer Science, or related field.
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