Company: Qualcomm India Private Limited
Job Area: Engineering Group, Engineering Group
Systems Engineering
General Summary:
Job Overview:
Qualcomm is a company of inventors that unlocked AI on Edge - ushering in an age of rapid acceleration in connectivity and new possibilities that will transform industries, create jobs, and enrich lives. But this is just the beginning. It takes inventive minds with diverse skills, backgrounds, and cultures to transform 5Gs potential into world-changing technologies and products. This is the Invention Age - and this is where you come in. QUALCOMM is the world's leading developer of next generation wireless and multimedia technology. Immediate opportunities exist in QUALCOMM's Multimedia Audio Systems Group to work in the area of Voice AI Power.
Responsibilities:
The candidate will be expected to work with a team of engineers to analyze, measure and Optimize Voice AI power for Models such as Automatic Speech recognition (ASR), Text-to-Speech (TTS), Multilingual Translation, Summarization, Language modeling and other Source separation and Speech/text generation models
Perform Competitive analysis of Voice AI Models Power with mutiple open source models
Support system design for optimized power on different form factors covering Mobile, XR, Compute and IoT
Work closely with other R&D and Systems team for system level analysis of power, and commercialization support
Requirements:
Strong programming skills in C/C++
Strong fundamentals of Power modeling and Power analysis
Experience working on System level power anlaysis and measurements
Knowledge of any ML frameworks pytorch, tensorflow, ONNX..
Knowledge of ML architectures and operators such as Transformers, LSTM, GRUs..
Experience working on Power measurement setups and Modeling Tools
Expertise in developing and debugging software on embedded platforms
Knowledge of Model quantization and compression techiques is a plus
knowledge of fixed point coding
Knowledge of computer architecture, operating systems, data structures, and basic algorithms
Experience working on any AI HW accelerator NPU or GPU is a plus
Experience with processor workload analysis. MIPS and memory optimization is a plus
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