Android AI ML Engineer - On-Device

Overview

On Site
Depends on Experience
Contract - W2

Skills

A/B Testing
Adaptability
Amazon SageMaker
Cloud Computing
Collaboration
Computer Hardware
Amazon Web Services
Android
Android Development
Generative Artificial Intelligence (AI)
Artificial Intelligence
Data Processing
Data Security
Decision-making
Encryption
Good Clinical Practice
Google Cloud Platform
IaaS
Java
Kotlin
Lifecycle Management
Machine Learning (ML)
Management
Microsoft Certified Professional
Mobile Applications
Mobile Security
Optimization
Orchestration
Performance Tuning
Privacy
PyTorch
Real-time
Regulatory Compliance
Storage
Systems Design
TensorFlow
Vertex
Workflow

Job Details

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., Google Cloud Platform, 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
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.