Overview Qualcomm is a company of inventors that unlocked 5G 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. You will join the CR&D team running machine learning models on and developing the SDK for Qualcomms Neural Signal Processor. Your focus will be on analyzing the functionality and performance of competing products and helping to define the roadmap and implementation for Qualcomm Qranium SDK solution. Additionally, you will participate in the porting of ML frameworks and software to Qranium and perform detailed analysis of overall Qranium SDK and neural network performance. You will be collaborating across internal teams within CR&D as well as with Qualcomms commercial division (QCT) covering multiple engineering disciplines including: software development, software architecture, systems and hardware. Direct customer interaction supporting development and productization of commercial solutions may also be required. The successful applicant should have a diverse skill set including a strong background in machine learning, performance testing and analysis, understanding of accelerator architectures and a passion to drive world-class solutions. All Qualcomm employees are expected to actively support diversity on their teams, and in the Company. Minimum Qualifications
Bachelor's degree in Engineering, Information Systems, Computer Science, or related field.
7+ years Software Engineering or related work experience.
3+ years experience with Programming Language such as C, C++, Java, Python, etc.
Hands-on experience with Deep Learning frameworks like SNPE, Keras, Caffe/Caffe2, TensorFlow, PyTorch, etc including performance work
Experience/understanding of NN architectures and model formats, including ONNX, Caffe2, and Tensorflow
Experience with machine learning algorithms and architectures, including CNNs, and RNNs/LSTMs
Knowledge of Linux infrastructure and development tools
Experience with statistical tools like R, scikit, MLLib, or similar
Experience profiling and optimizing software for CPUs and/or GPU applications
Degree in Machine Learning/AI, Statistics, Applied Mathematics, Computer Science, or similar quantitative discipline
Experience with Source Code and Configuration management tools such as git
Excellent communication (written and verbal) and positive interpersonal skills
Understanding of GPU and/or DSP architectures, familiarity with low-level hardware designs or assembly coding a plus
Good understanding of compilers, LLVM or similar preferred
Strong background in mathematical operations: linear algebra, fast math libraries a plus
Excellent analytical, development, and debugging skills