Artificial Intelligence Engineer

Key Responsibilities

• Contribute to building and optimizing speech model (ASR, TTS etc.) and application pipelines (Prompt, RAG, tool calling, service orchestration) to improve scenario performance and response stability.
• Participate in end to end development and integration of AI features for wearables, covering requirement decomposition, solution design, joint debugging/testing, and version iteration.
• Engage in on-device model deployment and performance optimization, including model conversion, quantization compression, inference acceleration, and resource tuning (latency, memory, power consumption).
• Support the engineering development of AI Agents, implementing capabilities such as task planning, tool invocation, and multi-turn memory in device scenarios.
• Collaborate with product, algorithm, system, and testing teams on data analysis, effect evaluation, issue diagnosis, and closed-loop improvement.
• Contribute to engineering best practices, including evaluation baselines, logging/monitoring, graceful fallback, release management, and stability assurance mechanisms.

• Requirements
• Bachelor's degree or above in Computer Science, Artificial Intelligence, Software Engineering, Electronic Information, Automation, or related fields.
• Solid understanding of Deep Learning architectures (Transformer, Conformer, RNN-T, BERT) and familiarity with mainstream ASR/speech technologies or LLM frameworks.
• Solid programming skills with proficiency in at least one of Python, C++, or Java.
• Familiar with at least one AI application development approach (e.g., large-model API integration, RAG, Prompt engineering, workflow orchestration).
• Interest in on-device AI engineering; familiarity with any of ONNX, TFLite, NCNN, MNN, or ONNXRuntime is a plus.
• Basic engineering debugging capabilities, able to independently diagnose common issues (performance fluctuations, API timeouts, resource anomalies, stability problems).