Developer Relations Engineer

Job Responsibilities 1. Collaborate with external developers and partners. Adopt tiling, quantization, pruning, LoRA, PEFT and other model optimization techniques to lightweight large foundation models, and ensure stable deployment and operation on edge, mobile and server devices. 2. Integrate mainstream software stacks and AI frameworks, and conduct performance tuning in advance to support partners with product launch. Perform in-depth performance analysis and debugging for overall solutions before the official release of hardware chips. 3. Work closely with R&D and product teams to identify and resolve issues existing in SDKs, runtimes, development tools and underlying hardware, so as to improve developer experience. 4. Compile technical guides, evaluation reports, white papers and other documents. Build the developer ecosystem via technical sharing, on-site demos and open source operations, and promote technologies for on-device inference and model deployment. Job Requirements 1. Possess a customer-oriented mindset. Be willing to engage with third-party developers and accept on-site work; capable of independently undertaking AI application and model projects. 2. Proficient in C/C++ and Python, with solid experience in embedded development. Skilled in full software stack debugging, performance troubleshooting and analysis on Android and Linux platforms. 3. Understand the principles of neural networks such as LLM and CNN, and be adept at model optimization and deployment technologies and tools. 4. Familiar with mainstream machine learning frameworks including PyTorch, LiteRT, TensorRT and Core ML, as well as model formats like ONNX and TFLite. Able to optimize runtimes to ensure production readiness of projects. 5. Possess excellent technical communication skills, capable of explaining complex technical solutions to audiences at different levels. Able to independently deliver various technical documents and analysis reports. 6. Enthusiastic about creating technical content. Prior experience in technical sharing, blog writing and open source participation is preferred. Preferred Qualifications 1. Candidates with development experience in automotive or robotics fields, and familiarity with Android Automotive, IVI, ADAS and related applications are highly preferred. 2. Knowledgeable about hardware system architecture, memory, bus, thermal design and other related areas. Experienced in system-level performance optimization for CPUs, NPUs and hardware accelerators is a plus. 3. Experience in edge-cloud integrated projects involving mobile/IoT devices and cloud platforms, and familiarity with cloud-native technologies such as containers, Kubernetes and serverless architecture will be an advantage. Benefits & Working Arrangements 1. Hybrid work mode is available. Teams can arrange working schedules flexibly based on business needs. 2. Comprehensive training system. You will get access to cutting-edge technologies including AI model optimization and edge-cloud deployment with broad career development prospects. 3. Flat management structure and friendly team atmosphere. Competitive compensation and benefits, including holiday benefits and paid annual leave.

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