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Lenovo is seeking an experienced Software Engineer to lead the integration and implementation of Small Language Model (SLM) inferencing for our next-generation AI systems onto Android devices. If you are passionate about making Smarter Technology For All, come help us realize our Hybrid AI vision! Responsibilities: Design, implement, and maintain core agent runtimes responsible for: Dynamic model loading and lifecycle management on Android devices Scheduling, prioritization, and queuing of model inference requests Information retrieval, data preprocessing, and context preparation pipelines Developing system integrations to support interoperability between Android applications, services, and AI runtime components Implementing security and privacy controls, including process isolation, app sandboxing, audit logging, and compliance with enterprise-grade mobile security standards Optimizing runtime performance for latency, throughput, and memory footprint across heterogeneous compute platforms (CPU, GPU, NPU/DSP) and across various vendor AI runtimes (e.g., Qualcomm AI Engine, MediaTek EdgeAI) Embedding safety and interpretability features into the stack, including guardrails, telemetry, and explainability mechanisms Contributing to platform reliability, including fault tolerance, error handling, and automated recovery strategies Collaborating with cross-functional teams (AI researchers, product managers, QA, and DevOps) to deliver robust, production-ready solutions Mentoring junior engineers by providing technical guidance, conducting code reviews, and supporting onboarding Authoring technical documentation and best practices, contributing to internal knowledge bases, design proposals, and architecture reviews Required Qualifications: Expertise in Android development, including Android SDK, NDK, AIDL, and Binder IPC Strong understanding of Android application and system security best practices (e.g., app sandboxing, SELinux, secure coding, permission models) Strong programming skills in Kotlin/Java for Android application and service integration Proficiency in C/C++ for Android NDK/system-level development Preferred Qualifications: Familiarity with mobile AI runtimes such as ONNX, TensorFlow Lite, Qualcomm AI Engine, and MediaTek EdgeAI Working knowledge of Python and deep learning frameworks such as PyTorch Strong problem-solving and debugging skills in complex, multi-threaded environments Experience with GGML, GGUF, and llama.cpp for local model inference Experience with Kotlin Multiplatform (KMP) or other cross-platform development frameworks Contributions to open-source AI runtimes, libraries, or Android utilities Background in performance optimization, compiler toolchains, or low-level hardware acceleration Experience building AI features for consumer mobile apps at scale #AAITC
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