FocusKPI is  seeking 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 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 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. Experience with signal processing and real-time ML logic 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. Experience in Android development using Kotlin and/or Java is nice to have Documentation is essential 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. Experience with  anomaly detection and behavioral modeling Experience with secure telemetry and backend integration Background in building real-time, data-driven features in mobile apps at scale. Model optimization for ARM/mobile hardware 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 , 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:

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