Android AI ML Engineer - Infrastructure

Mountain View, CA

FocusKPI

FocusKPI offers custom marketing analytics solutions and specialized data science support to optimize ROI and improve productivity. Among our areas of expertise are: personalization AI/ML solutions, measurement (MMM & MTA), customer sentiment...

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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
  • Proven experience in Android development (Kotlin/Java), with 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.
  • 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.

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 is 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**


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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Tags: APIs Architecture Classification Clustering Data governance Generative AI Java Machine Learning ML models PhD Pipelines Privacy PyTorch Security TensorFlow

Perks/benefits: Career development

Region: North America
Country: United States

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