Qualcomm Technologies (QCT) is the largest provider of chipset and software technology in the world, with chipsets powering the majority of all 3G/4G devices commercially available. QCT partners with nearly 100+ network operators around the globe and has the largest modem engineering team in the industry. QCT provides complete chipset solutions and integrated applications from the Launchpad suite of advanced technologies. Our integrated solutions offer device manufacturers reduced bill-of-materials costs, time-to-market, and development time. As a member of the 4G/5G technology software team, responsibilities will include identifying, scoping and understanding different ML use cases, building and integrating data pipelines for those use cases into the existing data mining framework along with SW/FW development. This role entails collaborating with different engineering teams within Qualcomm. This position gives the opportunity to develop & leverage strong expertise in software real time systems and cutting-edge cellular technologies that not only power the smart phones and computing markets but also the strong adjacent segments like automotive, healthcare & IoE.
Minimum Qualifications
- Bachelor’s degree in Engineering, Information Systems, Computer Science, or related field.
- 1+ years experience with Programming Language such as C, C++, Java, Python, etc.
Preferred Qualifications
- Master’s (with at least 2 years of experience) or PhD in Computer Science, Math, Statistics or related field
- Knowledge of variety of deep learning architectures like CNN, RNN/LSTM etc with hands on experience developing neural networks.
- Hands-on experience using ML frameworks such as PyTorch, TensorFlow, Keras, Caffe/Caffe2 etc.
- Experience working on Supervised and Unsupervised Machine Learning algorithms.
- Experience working on machine learning data pipelines for structured, unstructured and large datasets.
- Extensive programming in Python and C/C++.
- Basic real-time programming/software design and development.
- Experience in debugging complex software issues.
- Experience working with AWS tools like AWS Sagemaker is a plus.
- Experience with on-device deployment of ML models is a plus.
- Strong analytical and problem-solving skills.