NPU Library Software Engineer

This role involves designing and enhancing compute libraries for neural network operations, focusing on functional coverage and performance optimization on Rebellions' proprietary ISA. Key qualifications include a Master's degree in EE/CS, deep knowledge of neural network operations, strong troubleshooting and optimization skills, and proficiency in C++ and Python.

Must Have

• Master's or higher degree in Electrical Engineering, Computer Science, or a related field
• Thorough knowledge of neural network operations, from high-level concepts to low-level computation flow
• Excellent troubleshooting, problem-solving, and in-depth optimization skills
• Proficiency in C++ and Python programming languages

Good to Have

• Thorough knowledge of deep learning models for various applications, including vision, language, speech, etc.
• Experience in model/layer-level customization in terms of computation efficiency (e.g., sparsity, reduced precision, layer decomposition, etc.)
• Experience in architecture-specific parallel programming to accelerate target operations (e.g., SSE/AVX in x86, NEON in AArch, CUDA/OpenCL in GPU, etc.)
• A major in computer architecture field is preferred

Responsibilities and Opportunities

• Designing a compute library (such as blas, dnn, etc.) composed of various neural network operations, which are being accelerated on the rebellions' proprietary instruction set architecture (ISA)
• From a functionality perspective, enhancing the functional coverage of each operation by considering operation-specific constraints (e.g., tensor shape variation, precision loss handling, etc.)
• From a performance perspective, enhancing the utilization of the computational units in heterogeneous compute resources by considering operation-specific characteristics

Key Qualifications

• Master's or higher degree in Electrical Engineering, Computer Science, or a related field
• Thorough knowledge of neural network operations, not only for the high-level concepts but also for the low-level computation flow
• Excellent troubleshooting, problem-solving, in-depth optimization skills
• Proficiency in programming languages: C++, Python

Ideal Qualifications

• Thorough knowledge of deep learning models for various applications, including vision, language, speech, etc.
• Experience in model/layer-level customization in terms of computation efficiency (e.g., sparsity, reduced precision, layer decomposition, etc.)
• Experience in architecture-specific parallel programming to accelerate target operations (e.g., SSE/AVX in x86, NEON in AArch, CUDA/OpenCL in GPU, etc.)
• A major in computer architecture field is preferred

Application Process

• Document screening - On-line interview - On-site interview - Culture-fit interview - Compensation negotiation - Final acceptance
• The application process may vary by job, and may change depending on the schedule and circumstances.
• Application schedule and results will be individually notified via the email address provided during application.

Notes

• This announcement may close early if recruitment is completed.
• If there are false facts in the application, acceptance may be canceled.
• Recruitment may be restricted if legal qualifications required for recruitment and job performance are not met.
• Being a person of national merit or a person with a disability does not cause any disadvantage in the recruitment process.
• The scope of duties may be changed considering the candidate's overall career, experience, and other circumstances. If such a change is necessary, it will be communicated with the candidate at an appropriate time before the final acceptance notification.
• For recruitment-related inquiries, please contact the email address below.
• recruit@rebellions.ai