Software Engineer (Android)

Lenovo • Morrisville, NC

95d

About The Position

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!

Requirements

• 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.

Nice To Haves

• 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.

Responsibilities

• Design, implement, and maintain core agent runtimes responsible for dynamic model loading and lifecycle management on Android devices.
• Schedule, prioritize, and queue model inference requests.
• Develop information retrieval, data preprocessing, and context preparation pipelines.
• Develop system integrations to support interoperability between Android applications, services, and AI runtime components.
• Implement security and privacy controls, including process isolation, app sandboxing, audit logging, and compliance with enterprise-grade mobile security standards.
• Optimize runtime performance for latency, throughput, and memory footprint across heterogeneous compute platforms (CPU, GPU, NPU/DSP) and various vendor AI runtimes (e.g., Qualcomm AI Engine, MediaTek EdgeAI).
• Embed safety and interpretability features into the stack, including guardrails, telemetry, and explainability mechanisms.
• Contribute to platform reliability, including fault tolerance, error handling, and automated recovery strategies.
• Collaborate with cross-functional teams (AI researchers, product managers, QA, and DevOps) to deliver robust, production-ready solutions.
• Mentor junior engineers by providing technical guidance, conducting code reviews, and supporting onboarding.
• Author technical documentation and best practices, contributing to internal knowledge bases, design proposals, and architecture reviews.

What This Job Offers

• Job Type: Full-time
• Industry: Computer and Electronic Product Manufacturing