AI Application Engineer

Role Overview You will develop, optimize, and demonstrate end-to-end AI applications and reference designs on the proprietary RISC-V AI SoC and SDK. This includes benchmarking, demos, and workload enablement to showcase platform capabilities and provide ready-to-use examples for developers and customers. Key Responsibilities Develop and port AI workloads (CNN, Transformer, multimodal) using PyTorch, TensorFlow, and ONNX on the SDK. Create reference designs combining compiler, runtime, and kernel components. Develop SDK demos, tutorials, and reproducible benchmarking pipelines. Optimize models for performance, accuracy, and power efficiency. Collaborate with compiler, runtime, and framework teams to debug and tune workloads. Deliver performance analysis reports and reference application repositories. Collect usability feedback from internal and external developers. Qualifications 3 years above of experience in AI model development, optimization, or deployment. Strong hands-on with PyTorch, TensorFlow, or ONNX Runtime. Experience running AI workloads on GPU, NPU, or heterogeneous compute systems. Strong Python skills; C++ proficiency preferred. Preferred Attributes Familiarity with quantization, mixed precision, and compiler-based model optimization. Experience creating AI SDK demos, sample apps, or developer documentation. Understanding of CNN, transformer, and attention-based models.