Online Machine Learning Engineer for Mobile Apps
Description
๐จโ๐ป Online Machine Learning Engineer for Mobile Apps (Remote)
๐ Introduction: Build the Future of Mobile AI from Anywhere
Are you ready to architect intelligent mobile solutions that power millions of devices globally? As a Remote Online Machine Learning Engineer for Mobile Apps, you'll lead the development and deployment of cutting-edge ML models that enhance app performance, optimize user experience, and redefine personalization. This role is ideal for professionals seeking remote careers in mobile-focused machine learning, aiming to build a long-term path in work-from-home AI development, or passionate about reshaping the mobile AI space. You'll collaborate with world-class experts to deliver technology that shapes user interaction with digital environments.
๐ผ Job Snapshot
- Job Title: Online Machine Learning Engineer for Mobile Apps
- Annual Salary: $164,000
- Work Type: Fully Remote / Global Access
- Schedule: Flexible Hours / Full-Time
- Field: Artificial Intelligence, Mobile Engineering, Data Science
โจ Role Summary
๐ Engineering Intelligence at Scale
You will design scalable machine learning pipelines tailored for mobile platforms, ensuring real-time performance without compromising the user experience. From refining recommendation systems to enabling on-device speech recognition, your solutions will drive intelligent personalization and adaptability.
Key Contributions
- ๐ง Build robust end-to-end ML systems from experimentation to live deployment
- โ๏ธ Engineer inference-ready models that prioritize responsiveness and energy efficiency
- ๐ Extract meaningful features from noisy mobile data streams
- โป๏ธ Continuously improve models through real-world usage data
- ๐ฑ Partner with cross-disciplinary teams to deliver ML-enabled product features
๐ง Key Responsibilities
๐ Model Development & Optimization
๐ง ML Architecture Design
- Design ML architectures with low-latency, energy-aware performance for mobile
- Balance model complexity with device constraints
๐ Performance Evaluation
- Perform thorough offline analysis and real-time testing
- Use A/B tests and in-app feedback for continuous iteration
๐ Deployment & Integration
โ๏ธ Model Conversion and Compression
- Adapt models for mobile-ready formats: TensorFlow Lite, CoreML, ONNX
- Optimize footprint and runtime without sacrificing accuracy
๐ SDK and API Integration
- Work with app developers to embed ML features seamlessly
- Ensure scalable, secure integration pipelines
๐ Data Management & Feature Engineering
๐งน Data Collection and Preprocessing
- Develop ingestion systems for event logs, sensor data, and interaction history
- Ensure mobile-appropriate preprocessing techniques
๐ Feature Engineering
- Use domain insights to derive predictive mobile-specific features
- Emphasize compact, expressive features for inference efficiency
๐ Collaboration & Strategy
๐ค Cross-Functional Coordination
- Translate ML innovations into UX strategies and product solutions
- Be the technical point of contact for mobile-centric AI
๐ญ Strategic Leadership
- Guide sprint cycles, roadmap alignment, and model deployment strategy
- Maintain documentation for reproducibility and knowledge sharing
๐ง Required Skills & Experience
โ Core Technical Expertise
- 5+ years delivering production ML/AI models
- Minimum 2 years of mobile/edge ML experience
- Advanced Python and libraries: TensorFlow, PyTorch, JAX
- Familiarity with CoreML, TensorFlow Lite, and ONNX for on-device AI
- Understanding of Android/iOS ecosystems
๐ Broader Engineering Competencies
- Knowledge of federated learning, model pruning, and distillation
- Comfort with Git, CI/CD, and versioned model workflows
- Awareness of privacy, encryption, and compliance in mobile ML
๐ What Sets You Apart
๐ Unique Strengths and Mindset
- Passionate about continuous learning and innovation
- Skilled in simplifying complex ideas into actionable plans
- Committed to ethical, user-focused AI development
- Capable of transforming research insights into deployable products
๐ฑ Growth Opportunities & Perks
๐ Career Advancement
- Pathways to Principal ML Engineer, AI Architect, or Head of AI Engineering
๐ Team & Tools
- Collaborate on global AI programs
- Participate in proof-of-concepts, sandbox projects, and innovation labs
๐ Learning and Mentorship
- Funded access to AI summits, workshops, and upskilling platforms
- Dedicated mentorship and biannual career planning
๐ฌ Testimonials
"Building an ML engine for edge devices has been one of the most fulfilling parts of my career. I never thought I could make such a huge impact remotely." โ Rahul Verma, Senior ML Engineer
"The leadership here trusts us to innovate. Iโve learned more in the last year than in my previous five. Every idea is welcome and tested." โ Sneha Kapoor, Mobile AI Specialist
โ Ideal Candidate Profile
๐ Background & Attributes
- Degree in CS, Applied Math, Data Engineering, or relevant fields
- Experience deploying ML models in real-time environments
- Strong interest in edge computing and hybrid AI infrastructure
- Self-directed, organized, and capable of remote collaboration
๐ How This Role Supports the Mission
๐ผ Organizational Impact
Your work will elevate the intelligence of mobile apps, improving engagement, retention, and the overall digital experience. By optimizing AI features for real-time, ethical, and accessible use, you position the organization as a trailblazer in next-generation mobile intelligence.
๐ข Call to Action
โจ Ready to lead the charge in mobile AI innovation? Please apply now to become our next Online Machine Learning Engineer for Mobile Apps. Help shape the next chapter of mobile intelligence with us!
Published on: Apr 21, 2025