General Summary:
As a leading technology innovator, Qualcomm pushes the boundaries of what's possible to enable next-generation experiences and drives digital transformation to help create a smarter, connected future for all. As a Qualcomm Software Engineer, you will design, develop, create, modify, and validate embedded and cloud edge software, applications, and/or specialized utility programs that launch cutting-edge, world class products that meet and exceed customer needs. Qualcomm Software Engineers collaborate with systems, hardware, architecture, test engineers, and other teams to design system-level software solutions and obtain information on performance requirements and interfaces.
Minimum Qualifications:
As a leading technology innovator, Qualcomm pushes the boundaries of what's possible to enable next-generation experiences and drives digital transformation to help create a smarter, connected future for all. As a Qualcomm Software Engineer, you will design, develop, create, modify, and validate embedded and cloud edge software, applications, and/or specialized utility programs that launch cutting-edge, world class products that meet and exceed customer needs. Qualcomm Software Engineers collaborate with systems, hardware, architecture, test engineers, and other teams to design system-level software solutions and obtain information on performance requirements and interfaces.
Staff Engineer (AISW)
Job Location: Hyderabad
More details below:
Join the growing team at Qualcomm focused on advancing state-of-the-art in Machine Learning. The team uses Qualcomm chips’ extensive heterogeneous computing capabilities to allow inference of trained neural networks on-device without a need for connection to the cloud. Our inference engine is designed to help developers run neural network models trained in a variety of frameworks on Snapdragon platforms at blazing speeds while still sipping the smallest amount of power. See your work directly impact billions of devices around the world.
Ability to collaborate across a globally diverse team and multiple interests.
Machine Learning Engineer
Job Location: Hyderabad
More details below:
Join a new and growing team at Qualcomm focused on advancing state-of-the-art in Machine Learning. The team uses Qualcomm chips’ extensive heterogeneous computing capabilities. See your work directly impact billions of mobile devices around the world. In this position, you will be responsible for the development and commercialization of ML solutions like Snapdragon Neural Processing Engine (SNPE) and AI Model Efficiency Toolkit (AIMET) on Qualcomm SoCs. You will have expert knowledge of design, improvement, and maintenance of large AI software stacks using best practices.
Work Experience:
1.6-14 years of relevant work experience in software development (we have positions at multiple levels)
2.Live and breathe quality software development with excellent analytical and debugging skills. Strong understanding of Deep Learning and Machine learning theory and practice.
3.Experience with Deep learning model development. Data transformations, model training, model design, model optimization.
4.Familiarity with various deep learning architectures and problem domains like Computer Vision, Speech recognition, NLP etc.
5.Strong development skills in Python and C++. Experience with at least one machine learning framework like TensorFlow, ONNX, Pytorch, etc.
6.Understanding of software development and debugging in embedded environments.
7.Excellent communication skills (verbal, presentation, written)
8.Ability to collaborate across a globally diverse team and multiple interests.
Preferred Qualifications
1.Familiarity with neural network operators and model formats including PyTorch, ONNX, and Tensorflow.
2.Familiarity with neural network optimization techniques like graph optimization, quantization, pruning, knowledge distillation, network architecture search etc.
3.Strong understanding about embedded systems, system design fundamentals.
4.Well versed in version control tools like git
5.Experience with machine learning accelerators, optimizing algorithms for hardware acceleration cores, working with heterogeneous or parallel computing systems.
Educational Requirements
·Bachelor's/Master’s/PhD in Computer Science, Computer Engineering, or Electrical Engineering
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