A company is looking for an AI Research Engineer to optimize deep learning models for edge AI platforms.
Key Responsibilities
Research and develop quantization-aware training (QAT) and post-training quantization (PTQ) techniques for deep learning models
Design and optimize efficient inference algorithms for AI workloads, focusing on latency, memory footprint, and power efficiency
Collaborate with hardware engineers to optimize model execution for edge devices and NPUs
Required Qualifications
Master's or Ph.D. in Computer Science, Electrical Engineering, or a related field
Strong expertise in deep learning, model optimization, and numerical precision analysis
Hands-on experience with model quantization techniques (QAT, PTQ, mixed precision)
Proficiency in Python, C++, CUDA, or OpenCL for performance optimization
Understanding of low-level hardware acceleration (e.g., SIMD, AVX, Tensor Cores, VNNI)
Ai Research Engineer • Ontario, California, United States