Android AI ML Engineer - On-Device
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.
- 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:
- Specialized experience in catering to mobile devices. Mobile is a very resource constrained system.
- Prior experience in optimizing ML solutions on on-device.
- Experience in quantifying or optimizing on-device and handling privacy like federated learning or something similar is preferred.
- Experience in TensorFlow Lite (TFLite), Edge device, and mobile device optimization.
- 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.
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