Android AI/ML Engineer (On-Device) | Mountain View, CA - Onsite

Overview

On Site
Accepts corp to corp applications
Contract - W2
Contract - Independent
Contract - 6 month(s)

Skills

device
android
TensorFlow Lite
ML Kit
GenAI APIs
MediaPipe
PyTorch Mobile

Job Details

Cohesive Technologies is a global IT Services & Solutions company providing IT Staffing Services and Application Development Services necessary for technology leaders to deliver business value. We help our people and clients succeed by leveraging our expertise, deep industry and market knowledge, proprietary assessment tools and techniques and project delivery methodologies. Through relationships with thousands of specialized professionals, we bring an unparalleled ability to match talent with opportunities by assessing, recruiting, developing and engaging the best and brightest people for our clients. We combine broad geographic presence, world-class solutions and a tailored, consultative approach to help our people and clients achieve higher performance and outstanding results.

Position Title: Android AI/ML Engineer (On-Device)

Location: Mountain View, CA (On-site)

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., Google Cloud Platform, 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

Cohesive Technologies is an equal access/equal opportunity employer and does not discriminate on the basis of age, color, disability, marital status, national origin, race, religion, sex, sexual orientation, veteran status or any other classification prescribed by applicable law.


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