• Android AI ML Engineer - Infrastructure

    FocusKPI Inc. (Mountain View, CA)


    FocusKPI is looking for an Android AI ML Engineer - Infrastructure to join one of our clients, a high-tech SaaS company.

     

    The client is seeking an experienced Android AI/ML Engineer - Infrastructure to develop advanced on-device machine learning systems that enable secure, adaptive, and scalable intelligence across mobile devices. The role emphasizes building intelligent, adaptive, and privacy-preserving ML systems that operate efficiently within the constraints of mobile environments.

     

    The ideal candidate will have strong experience in designing real-time, context-aware inference systems that can respond dynamically to local data patterns and behaviors.

     

    Work Location:  Mountain View, CA (on-site 4 days a week)

     

    Duration: 6-month contract; hybrid role

     

    Pay Range: 80/hr to $93/hr

     

    No C2C resumes are considered

    Responsibilities:

    + Design, develop, and deploy on-device machine learning models optimized for Android, ensuring low latency and minimal resource consumption.

    + Build robust and scalable ML pipelines using Android-native frameworks such as:

    + TensorFlow Lite

    + ML Kit (including GenAI APIs)

    + MediaPipe

    + PyTorch Mobile

    + Implement local signal aggregation and real-time pattern recognition logic to enable responsive in-app actions driven by on-device inference.

    + Architect systems that support telemetry, secure logging, and privacy-first feedback collection for monitoring and evaluation.

    + Apply model compression and optimization techniques (e.g., quantization, pruning, distillation) to meet mobile performance constraints.

    + Develop secure, privacy-first solutions where all data processing and ML inference occur strictly on-device, with no external data exposure.

    + Enable mechanisms for continuous local learning and model updates using device-resident data and signals, without compromising privacy.

    + Ensure integration with Android’s security model and collaborate with platform and product teams to deploy AI features safely at scale.

    Qualifications:

    + 5-7 years of experience with a Master's degree, 3+ years of experience with a PhD

    + A candidate with a strong on-device ML experience is highly prioritized and required

    + A strong understanding of system architecture, resource management, and performance tuning.

    + Hands-on expertise with on-device ML frameworks including TensorFlow Lite, ML Kit, MediaPipe, and PyTorch Mobile.

    + Solid foundation in machine learning and signal processing techniques, such as time-series modeling, clustering, classification, and real-time event detection.

    + Strong knowledge of mobile data handling and Android security practices, including permissions, sandboxing, and secure data storage.

    + Strong experience with model optimization and backend integration

    + Understanding of privacy-preserving learning techniques and data governance in mobile environments.

    + Familiarity with secure data handling on Android, including encrypted storage, permissions, sandboxing, and secure compute enclaves.

    + Experience with telemetry systems and evaluation pipelines for monitoring model performance on-device at scale.

    + Experience in Android development (Kotlin/Java) is good to have

    Desired qualifications:

    + Experience building ML-driven mobile applications in domains requiring user personalization, privacy, or security.

    + Understanding of real-time data processing and behavioral modeling on resource-constrained edge devices.

    + Knowledge of on-device learning techniques, federated learning, or personalization methods.

    + Prior contributions to systems using federated learning, differential privacy, or local fine-tuning of models are a plus

    + Experience with backend infrastructure for model management (e.g., model registries, update orchestration, logging frameworks) is a plus.

    + Prior work with anomaly detection or behavioral modeling in resource-constrained environments is a plus.

    + Experience developing responsive systems capable of monitoring local context and dynamically triggering actions based on model outputs is a plus

    + Experience optimizing models for ARM architectures is a plus

     

    No C2C resumes are considered, and  avoid Android developers for this role.

     

    Thank you!

     

    FocusKPI Hiring Team

     

    Founded in 2010, FocusKPI, Inc. (FocusKPI) is a data science and technology firm specializing in predictive analytics practice and methodologies. FocusKPI is a US company headquartered in Silicon Valley, California, with an East Coast office in Boston, Massachusetts.

     

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