Android AI ML Engineer - Infrastructure
Mountain View, CA
Contract Senior-level / Expert USD 186K+
FocusKPI
FocusKPI offers custom marketing analytics solutions and specialized data science support to optimize ROI and improve productivity. Among our areas of expertise are: personalization AI/ML solutions, measurement (MMM & MTA), customer sentiment...The client is seeking an experienced Android AI/ML Engineer - Infrastructure to develop advanced on-device machine learning systems that enable secure, adaptive, and scalable intelligence across mobile devices. The role emphasizes building intelligent, adaptive, and privacy-preserving ML systems that operate efficiently within the constraints of mobile environments.
The ideal candidate will have strong experience in designing real-time, context-aware inference systems that can respond dynamically to local data patterns and behaviors.
Work Location: Mountain View, CA (on-site 4 days a week)
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.
Qualifications:
- 5-7 years of experience with a Master's degree, 3+ years of experience with a PhD
- Proven experience in Android development (Kotlin/Java), with 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.
- 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.
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 is 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**
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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Tags: APIs Architecture Classification Clustering Data governance Generative AI Java Machine Learning ML models PhD Pipelines Privacy PyTorch Security TensorFlow
Perks/benefits: Career development
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