What are the responsibilities and job description for the Machine Learning Research Engineer (AI/ML) – TensorFlow Lite, ML Kit, PyTorch position at The Mom Project?
Our Customer is a Silicon Valley-based company that is engaged in researching emerging technologies.
We are seeking a contract Machine Learning Research 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.. This role is a hybrid setup (4 days on-site and 1 day remote/week) in Mountain View, CA (on-site preferred).
Responsibilities
Contractor benefits are available through our 3rd Party Employer of Record (Available upon completion of waiting period for eligible engagements)
Benefits include: Medical, Dental, Vision, 401k.
An Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or protected veteran status and will not be discriminated against on the basis of disability.
We are seeking a contract Machine Learning Research 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.. This role is a hybrid setup (4 days on-site and 1 day remote/week) in Mountain View, CA (on-site preferred).
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 Generative AI APIs), MediaPipe, and PyTorch Mobile.
- Develop efficient on-device data pipelines and inference mechanisms that support real-time decision-making.
- Apply model optimization techniques including quantization, pruning, and distillation to enhance performance on mobile hardware.
- Ensure all data processing and inference occur strictly on-device to support a privacy-first design approach.
- Collaborate with backend teams to integrate with cloud-based model orchestration systems such as MCP, enabling model versioning, remote updates, telemetry collection, performance monitoring, and rollout infrastructure including A/B testing.
- Implement secure local storage, encrypted data handling, and telemetry pipelines that adhere to privacy and compliance requirements.
- Support adaptive model behavior through on-device fine-tuning, personalization, or federated learning workflows.
- 5-7 years of experience with a Masters degree, 3 years of experience with a PhD
- 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.
- 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.
Contractor benefits are available through our 3rd Party Employer of Record (Available upon completion of waiting period for eligible engagements)
Benefits include: Medical, Dental, Vision, 401k.
An Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or protected veteran status and will not be discriminated against on the basis of disability.
