Android AI ML Engineer - Infrastructure
FocusKPI is looking for an Android AI ML Engineer - Infrastructure to join one of our clients, a high-tech SaaS company.
Duration: 6-month contract; hybrid role
Pay Range: 80/hr to $93/hr **No C2C resumes are considered** 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
- Implement local signal aggregation and real-time pattern recognition logic to enable responsive in-app actions driven by on-device inference.
- Architect systems that support telemetry, secure logging, and privacy-first feedback collection for monitoring and evaluation.
- Apply model compression and optimization techniques (e.g., quantization, pruning, distillation) to meet mobile performance constraints.
- Develop secure, privacy-first solutions where all data processing and ML inference occur strictly on-device, with no external data exposure.
- Enable mechanisms for continuous local learning and model updates using device-resident data and signals, without compromising privacy.
- Ensure integration with Android’s security model and collaborate with platform and product teams to deploy AI features safely at scale.
- 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 strong understanding of system architecture, resource management, and performance tuning .
- Hands-on expertise with on-device ML frameworks including TensorFlow Lite, ML Kit, MediaPipe, and PyTorch Mobile.
- Solid foundation in machine learning and signal processing techniques , such as time-series modeling, clustering, classification, and real-time event detection.
- Strong knowledge of mobile data handling and Android security practices , including permissions, sandboxing, and secure data storage.
- Strong experience with model optimization and backend integration
- Understanding of privacy-preserving learning techniques and data governance in mobile environments.
- Familiarity with secure data handling on Android, including encrypted storage, permissions, sandboxing, and secure compute enclaves.
- Experience with telemetry systems and evaluation pipelines for monitoring model performance on-device at scale.
- Experience in Android development (Kotlin/Java) is good to have
Desired qualifications:
- Experience building ML-driven mobile applications in domains requiring user personalization, privacy, or security.
- Understanding of real-time data processing and behavioral modeling on resource-constrained edge devices.
- Knowledge of on-device learning techniques, federated learning , or personalization methods.
- Prior contributions to systems using federated learning, differential privacy, or local fine-tuning of models are a plus
- Experience with backend infrastructure for model management (e.g., model registries, update orchestration, logging frameworks) is a plus.
- Prior work with anomaly detection or behavioral modeling in resource-constrained environments is a plus.
- Experience developing responsive systems capable of monitoring local context and dynamically triggering actions based on model outputs is a plus
- Experience optimizing models for ARM architectures 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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