Android AI/ML Engineer - On-Device

37 Days Old

Job Description

Job Description

Android AI/ML Engineer (On-Device)
We are 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.
Key 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.
Technical Requirements:
  • 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.
Preferred 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.
  • 5-7 years of experience with a Masters degree, 3+ years of experience with a PhD
Compensation: $70 - $93.19
ID#: 36129206
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Location:
Mountain View
Category:
Technology

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