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Android AI ML Engineer - Infrastructure
Android AI ML Engineer - InfrastructureFocuskpi • Mountain View, California, United States
Android AI ML Engineer - Infrastructure

Android AI ML Engineer - Infrastructure

Focuskpi • Mountain View, California, United States
30+ days ago
Job type
  • Temporary
Job description

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.

    NOTICE : Please be aware of fraudulent emails regarding job postings, job offers and fake checks. FocusKPI's recruiting team will strictly reach out via @focuskpi.com email domain. If you have received fraudulent emails now or in the past, please report it to https : / / reportfraud.ftc.gov / .

    The domain @focuskpijobs.com is fraudulent and not related to FocusKPI. Please do not not reply or communicate to anyone with @focuskpijobs.com.

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