Android AI / ML Engineer - On-Device
ApolisFremont, CA, United States9 days ago
Job type
- Full-time
Job descriptionML Kit (including GenAI APIs) MediaPipe PyTorch Mobile Optimize models using techniques like quantization, pruning, and distillation to meet mobile performance targets. Develop context-aware, real-time inference systems and data pipelines on-device. Implement privacy-first architecture, ensuring all data processing and inference is local. Collaborate with backend / cloud teams to integrate model orchestration systems (e.g., MCP, Vertex AI, SageMaker) for : Telemetry and performance monitoring A / B testing and rollout strategies Implement secure storage and encrypted data handling in line with privacy and compliance standards. Support adaptive model behavior using on-device personalization, federated learning, or similar privacy-preserving techniques. Strong Android development experience using Kotlin and / or Java Proficiency with on-device ML tools : ML Kit MediaPipe PyTorch Mobile Solid understanding of mobile constraints : Low-latency processing Model size and resource optimization Experience in integrating mobile apps with backend / cloud systems for : Secure telemetry and data analytics Knowledge of Android security best practices, including sandboxing, permissions, encryption, and local data protection Experience with federated learning, differential privacy, or on-device personalization Familiarity with cloud infrastructure (e.g., AWS, GCP) and ML deployment workflows Background in mobile AI features like anomaly detection, behavioral modeling, or privacy-focused applications Experience with model orchestration platforms such as MCP, Vertex AI, or SageMaker Master's degree with 5-7 years of relevant experience, or PhD with 3 years of relevant experience Preferred : Less than 10 years of total professional experience On-site presence preferred - at least 4 days / week in Mountain View, CA Standard business hours, minimal overtime except during key sprints 1 Technical Phone Screen 2 Virtual Technical Interviews Contract role with high potential for extension Strong possibility of full-time conversion based on performance and business needs TensorFlow Lite (TFLite) ML Kit MediaPipe PyTorch Mobile On-device machine learning Mobile ML pipeline Edge AI Model quantization / pruning / distillation Real-time inference Federated learning Differential privacy Telemetry integration Secure Android development Model orchestration Cloud-integrated ML (e.g., Vertex AI, SageMaker, MCP)
Location :
Mountain View, CA (On-site preferred, at least 4 days / week)
Position Summary :
We are looking for a highly capable engineer to design and deploy real-time, on-device machine learning solutions for mobile devices. This role focuses on developing privacy-first, resource-optimized ML systems that operate directly on Android hardware, supporting high-impact AI applications in real-world environments.
The ideal candidate brings deep technical expertise in on-device intelligence and mobile ML pipelines, and thrives in fast-paced environments that demand performance, security, and adaptability.
Key Responsibilities :
- Design and deploy efficient on-device ML models tailored for Android platforms.
- Build end-to-end ML pipelines using :
TensorFlow Lite
Model delivery and remote updates
Technical Requirements :
Must-Have Skills :
TensorFlow Lite
Real-time inference
Model lifecycle management
Nice-to-Have Skills :
Education & Experience :
Work Schedule :
Interview Process :
Position Type & Growth Potential :
Core Technical Keywords (for resume alignment) :
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Android Engineer • Fremont, CA, United States
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