About the Role
Develop and maintain machine learning models that power core services, working cross-functionally to integrate intelligent features into large-scale distributed systems.
Responsibilities
- Build and optimize machine learning models for real-time decision making
- Collaborate with engineering teams to integrate models into production systems
- Evaluate model performance using statistical methods and metrics
- Work with large-scale datasets to train and validate machine learning systems
- Design data pipelines to support model training and inference
- Improve model accuracy through iterative experimentation
- Monitor deployed models for performance degradation
- Troubleshoot issues in model pipelines and inference systems
- Contribute to model versioning and deployment frameworks
- Ensure models meet scalability and latency requirements
- Work with distributed computing environments for training
- Implement model explainability and fairness checks
- Support A/B testing for model validation
- Document model design and implementation decisions
- Stay current with advancements in machine learning research
- Optimize models for cost and efficiency
- Collaborate on defining data labeling requirements
- Ensure compliance with data privacy standards
- Participate in code and design reviews
- Support incident response for model-related issues
- Work with product teams to define ML-driven features
- Contribute to internal machine learning tooling
- Help define best practices for model deployment
- Assist in setting up monitoring for model drift
- Engage in technical planning for long-term ML initiatives
Nice to Have
- Master’s or PhD in machine learning or related field
- Experience with large-scale model training
- Background in communications or networking systems
- Contributions to open-source machine learning projects
- Experience with MLOps platforms
- Knowledge of edge computing for ML inference
- Familiarity with regulatory requirements for AI systems
- Experience mentoring junior engineers
- Published work in machine learning conferences or journals
- Leadership in technical project planning
Compensation
Competitive salary with equity and benefits
Work Arrangement
Hybrid or remote options available
Team
Part of a global engineering team focused on scalable communication platforms
Why This Role Matters
Machine learning is central to improving the reliability and intelligence of communication systems. This role directly impacts how users interact with global messaging and calling infrastructure.
What You’ll Do
- Design and implement machine learning solutions that process vast amounts of communication data
- Work closely with infrastructure teams to ensure models scale efficiently
- Drive improvements in model accuracy and system responsiveness
Available for qualified candidates
