Title: Mobile AI/ML Engineer – On-Device
Location: Mountain View, CA 
Duration: 6 months, with potential extension

Position Summary:
We are looking for a highly capable Android AI/ML Engineer 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

 

• 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.

Technical Requirements:

• Proficiency in Android development using Kotlin and/or Java with 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.
• 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.

Preferred Qualifications:

• 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.
• Background in building real-time, data-driven features in mobile apps at scale.
• 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.
• 5-7 years of experience with a Masters degree, 3+ years of experience with a PhD
   

  

 


At SPECTRAFORCE, we are committed to maintaining a workplace that ensures fair compensation and wage transparency in adherence with all applicable state and local laws. This position’s starting pay is: $80.00/hr.