Android AI/ML Engineer - On-Device

Position Summary:

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

Primary Job Duties :
Build and deploy real-time, on-device ML systems using TFLite, ML Kit, and similar frameworks

Research and design full ML pipelines tailored to mobile constraints

Implement signal aggregation and context-aware inference for in-app intelligence

Apply model compression techniques to meet mobile performance targets

Integrate with secure logging, telemetry, and evaluation infrastructure

Ensure privacy-first design with all inference and data processing performed on-device
Must-haves:
On-device ML frameworks (TFLite, ML Kit, PyTorch Mobile)

Signal processing and real-time ML logic
Nice-to-haves:

• Model orchestration
• Federated learning, anomaly detection, behavioral modeling
• Model optimization for ARM/mobile hardware
• Experience with secure telemetry and backend integration

Education:

5-7 years of experience with a Master s degree, 3+ years of experience with a PhD