AI/DSP Kernel Optimization Engineer

We are looking

for an AI/DSP Kernel Optimization Engineer to develop and optimize AI inference

kernels, analyze application performance, and integrate optimized kernels into

AI inference pipelines. The role involves low-level C/C++ optimization,

SIMD/vectorization, profiling, debugging, and close collaboration with hardware

and software teams to improve overall inference performance.

Responsibilities:

• Develop and optimize AI inference kernels using

C/C++.

• Optimize kernels for different data types,

including INT8, INT16, BF16, and FP32.

• Perform SIMD/vectorization, intrinsics, memory

optimization, and performance tuning.

• Profile and analyze application performance to

identify optimization opportunities.

• Debug and resolve functional and performance

issues.

• Integrate optimized kernels into the AI inference

pipeline.

• Work closely with hardware and software teams to

improve overall inference performance.

Requirements

Education:

B.E.,

B.Tech., M.E., M.Tech., or equivalent.

Technical Skills (Must haves):

• Good knowledge of C/C++ programming.
• Basic understanding of AI/Deep Learning models

and inference.

• Experience with DSPs, hardware accelerators, or

similar compute platforms.

• Knowledge of SIMD/vectorization, intrinsics, and

low-level software optimization.

• Good profiling, debugging, and performance

analysis skills.

Need to have (Can be bridged):

• Understanding of computer architecture and memory

optimization.

Good to have (Not essential):

• Experience in AI/ML inference optimization.
• Knowledge of different numerical data types such

as INT8, INT16, BF16, and FP32.

• Familiarity with performance profiling and

benchmarking tools.

Preferred Qualifications (Optional):

• Experience with C7x DSP, HWA-MMA, or similar

hardware accelerators.

• Hands-on experience optimizing inference

workloads for DSPs or specialized compute platforms.