Machine Learning Engineer, Edge AI

What You’ll Need

Strong Python, PyTorch and ONNX experience developing, training, evaluating, and deploying machine learning models. Deep understanding of modern AI architectures including CNNs, Transformers, state-space models, and other emerging neural network approaches. Experience optimizing, deploying and debugging models across a wide spectrum of edge devices, from ultra-constrained microcontrollers and DSPs to high-performance AI accelerators and GPUs. Experience developing machine learning solutions for one or more sensing domains, including time-series signals, audio, computer vision, or ultrasonic sensing. Hands-on experience with model compression and deployment techniques such as quantization, pruning, graph optimization, and operator/kernel optimization. Practical experience translating research concepts into production-quality systems. Strong understanding of model performance tradeoffs involving latency, memory footprint, power consumption, and accuracy. 4+ years of industry and/or academic experience in machine learning research, model development, or AI systems engineering. Nice to Have CUDA development and GPU optimization experience. Experience with TensorRT, ONNX Runtime, TVN, IREE, or similar inference frameworks. Experience with TinyML, embedded inference runtimes, or DSP programming. Familiarity with multimodal AI systems.

onsemi is excited to share the base salary range for this position i$120,000 - $170,000 exclusive of fringe benefits or potential bonuses. The final pay rate for the successful candidate will depend on geographic location, skills, education, experience, and/or consideration of internal equity of our current team members. We also offer a competitive benefits package