Android AI ML Engineer - On-Device

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 - On-Device to join one of our clients, a high-tech SaaS company.

The client is looking for a highly capable Android AI/ML Engineer - On-Device to help build intelligent, privacy-first mobile systems that can detect, respond to, and learn from dynamic real-world conditions. This role involves deploying resource-efficient ML models directly on Android devices, combined with backend integration for model management, telemetry, and secure update delivery.
The ideal candidate has a strong background in on-device intelligence and cloud-integrated systems, especially in applications that require responsiveness, adaptability, and strict privacy controls.

Work Location:  Mountain View, CA (on-site 4 days a week)
Duration: 6-month contract; hybrid role
Pay Range: 80/hr to $93/hr

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
  • Build robust and efficient on-device data pipelines and inference mechanisms for real-time decision-making.
  • Apply model optimization techniques such as quantization, pruning, and distillation for performance on mobile hardware.
  • Ensure privacy-first design by performing all data processing and inference strictly on-device.
  • Collaborate with backend teams to integrate with cloud-based model orchestration systems (e.g., MCP or similar) for:
    • Model versioning, delivery, and remote updates
    • Telemetry collection and model performance monitoring
    • Rollout and A/B testing infrastructure
  • Implement secure local storage, encrypted data handling, and telemetry pipelines that meet privacy and compliance standards.
  • Support adaptive model behavior through on-device fine-tuning, personalization, or federated learning workflows.

Qualifications:
  • 5-7 years of experience with a Masters degree, 3+ years of experience with a PhD
  • Proficiency in Android development using Kotlin and/or Java with deep understanding of app architecture, background processing, and system APIs.
  • Hands-on experience with on-device ML frameworks: TensorFlow Lite, ML Kit, MediaPipe, PyTorch Mobile.
  • Solid understanding of mobile performance optimization, including model size, memory usage, and latency.
  • Proven ability to integrate Android apps with backend/cloud systems for:
  • Model lifecycle management (delivery, updates, rollback)
  • Logging, telemetry, and analytics
  • Experience with secure Android development, including permissions, sandboxing, encryption, and local data protection.
  • Strong understanding of privacy-first ML system design and local-only data processing.

Desired qualifications:

  • Experience working with model orchestration platforms (e.g., MCP, Vertex AI, SageMaker, or internal tools).
  • Familiarity with federated learning, on-device personalization, or differential privacy.
  • Background in building real-time, data-driven features in mobile apps at scale.
  • Familiarity with cloud infrastructure (e.g., GCP, AWS) for ML model deployment and monitoring.
  • Previous work in high-sensitivity domains such as identity, privacy, mobile security, or regulated industries 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: A/B testing APIs Architecture AWS Data pipelines GCP Generative AI Java Machine Learning ML models Model deployment PhD Pipelines Privacy PyTorch SageMaker Security TensorFlow Testing Vertex AI

Region: North America
Country: United States

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