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Qualcomm AI Software Engineer Core Multiple levels 
Taiwan, Taipei, Taipei 
38062687

23.06.2024

Job Area:

Engineering Group, Engineering Group > Machine Learning Engineering

The Person

Developing in the core libraries for AI workload on NPU. Having strong sense and knowledge of fine-grained AI operation performance analysis/optimization, and solid analytical and problem-solving skills.

Key Responsibilities

· Design, implement, optimize, profiling, analysis AI computing operations running on Qualcomm NPU.

· Deliver high-quality code working with open-source software communities.

· Work with key technical specialists across Qualcomm, our partners and/or customers to improve libraries for commercial use cases and/or industrial benchmarks.

Qualifications(for new grad)

· Master's degree in Computer Science, Electrical Engineering, or related field.

· Proficiency in programming languages such as C, C++, or Python.

· Strong knowledge of Object-Oriented Programming, data structures, algorithms and operating system.

· Self-motivated and capable of working independently with minimal oversight.

Minimum Qualifications(for experienced engineers)

· Bachelor's degree in Computer Science, Electrical Engineering, or a related field.

· Proficiency in languages like C++, CUDA, or OpenCL for GPU programming.

· Understanding of GPU/DSP/NPU architectures and parallel programming concepts.

· Familiarity with embedded systems and constraints related to edge devices.

· Experience in low-level programming for efficient hardware utilization.

· Knowledge of optimizing algorithms and libraries for GPU/DSP/NPU execution.

· Ability to analyze and optimize performance bottlenecks in GPU/NPU code.

· Proficiency with version control systems like Git and software development tools like Gerrit and JIRA.

Preferred Qualifications(for experienced engineers)

· Master's or Ph.D. in Computer Science, Electrical Engineering, or a related field.

· Familiarity with frameworks such as TensorFlow, PyTorch for DSP/GPU/NPU integration.

· Understanding of mainstream ML runtime frameworks formats and their runtime environments.

· Experience in optimizing code specifically for different DSP/GPU/NPU architectures.

· Understanding of machine learning and deep learning concepts for efficient utilization of hardware.

· Proven experience in fine-tuning performance-critical applications on edge devices.

· Knowledge of hardware-software co-design principles for edge devices.

· Proficiency in using tools for debugging and profiling GPU/NPU code.

· Strong communication skills to collaborate with hardware engineers and communicate complex technical concepts effectively.

Expertise in at least one of the following areas

· DSP software development and algorithm implementation: Proficiency in designing and implementing algorithms for Digital Signal Processing (DSP) in software.

· OpenCL programming and debugging: Experience in programming and debugging using OpenCL, particularly for parallel computing applications.

· Performance profiling and optimization for parallel computing: Strong understanding and practical experience in profiling and optimizing performance for parallel computing tasks.

· Image processing, computer vision, and object/face detection specifically: Expertise in image processing, computer vision techniques, and specialized knowledge in object/face detection methodologies.

· Understanding compiler technology: Familiarity with ML compilers such as TVM/Glow/XLA, as well as experience in LLVM/GCC backend development, optimization analysis, and implementation is highly advantageous.

· AI experience: Knowledge of Deep Learning/CNN fundamentals, proficiency in training neural networks to solve real-world problems, and familiarity with frameworks like TensorFlow/PyTorch are considered strong assets for this role.

Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.