Job description
AI Vision Processors For Edge Applications Our solutions make cameras smarter by extracting valuable data from high-resolution video streams. Job Description Responsibilities Optimize CNN, Transformer, and related models for our hardware architecture and deployment constraints. Build conversion tooling from Py. Torch / ONNX to chip-executable representations, supporting automated model deployment pipelines.
Develop an edge AI runtime covering model loading, task scheduling, and memory management, with multi-task parallel inference. Support customer model porting and performance tuning, and deliver tailored AI solutions where needed. Contribute to technical documentation and standards: write specifications and best practices, and help the team capture and share technical knowledge.
Requirements
Bachelor’s degree or above in Computer Science, Electrical Engineering, or a related field, with 2+ years of experience in embedded AI development. Strong C/C++ and Python; hands-on embedded system development and debugging. Solid familiarity with deep learning frameworks (Py. Torch / ONNX) and the end-to-end model deployment workflow.
Understanding of CNN and Transformer architectures; model optimization or operator/kernel development experience is a plus. Experience in edge AI deployment, LLM serving / efficiency (e.g. vLLM-class stacks), or AI agent development is a plus. Strong cross-team collaboration and problem-solving; ability to narrow down and resolve complex technical issues quickly.