Qualcomm India Private Limited
Engineering Group, Engineering Group > Systems Engineering
General Summary:
Job Overview:
Responsibilities:
- The candidate will be expected to work with a team of engineers to design, implement and integrate ML framework for Qualcomm's Low power ML accelerator.
- Design, implement, integrate, and test kernels for ML operators for HW accelerator.
- Create test framework for validating end-end ML Software and ML Model performance
- Work closely with other R&D and Systems team for ML model optimizations and system integration, use case testing and commercialization support
- Requirements:
- Strong programming skills in C/C++, Python
- Expertise in developing and debugging software on embedded platforms
- Knowledge of ML operators such as Transformers, LSTM, GRUs..
- Knowledge of software design patterns and multi-threaded programming, Eg POSIX or PTHREADS
- Knowledge of computer architecture, operating systems, data structures, and basic algorithms
- knowledge of fixed point coding
- Knowledge of any ML frameworks pytorch, tensorflow, ONNX..
- Knowledge of Model quantization and compression techiques is a plus
- Working on ML inference optimizations is a plus
- Experience working on any AI HW accelerator (NPU) is a plus
- All Qualcomm employees are expected to actively support diversity on their teams, and in the Company.
- Proven ability to work in a dynamic, multi-tasked environment
- Self-starter who likes to be challenged and solve tough complex problems
- Excellent verbal and written communication and presentation skills.
- Quick learner, self-motivated, able to work independently and a Team player.
- Aspiration for excellence.
- Working in cross disciplinary, geographically-dispersed teams
Educational Qualification:
- Bachelor's/Master’s/PhD degree in Engineering, Electronics and communication, Computer Science or related filed.
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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