About the Role
Design and implement machine learning models to improve search relevance, ranking accuracy, and personalized user experiences across digital platforms.
Responsibilities
- Develop scalable machine learning models for search and recommendation systems
- Optimize ranking algorithms to improve result relevance
- Apply natural language processing techniques to query understanding
- Analyze user behavior data to enhance personalization features
- Collaborate with data scientists to refine feature engineering
- Evaluate model performance using statistical methods
- Deploy models into production environments
- Monitor model behavior and retrain as needed
- Work with engineering teams to integrate ML components
- Improve data pipelines for training and inference
- Research emerging techniques in information retrieval
- Implement A/B testing frameworks for model validation
- Ensure models meet latency and scalability requirements
- Troubleshoot issues in live machine learning systems
- Maintain documentation for models and workflows
- Stay current with advancements in ML and AI
- Support data labeling and annotation efforts
- Design experiments to measure user engagement impact
- Integrate third-party data sources when necessary
- Apply deep learning methods where appropriate
- Balance accuracy with computational efficiency
- Contribute to code reviews and system design
- Ensure compliance with data privacy standards
- Collaborate on cross-functional product initiatives
- Optimize for multilingual and multicultural contexts
Nice to Have
- Master's or PhD in a technical field
- Published research in ML or NLP domains
- Experience with large-scale search systems
- Knowledge of transformer-based models
- Familiarity with reinforcement learning
- Experience in real-time inference systems
- Contributions to open-source ML projects
- Background in e-commerce or content platforms
- Prior work with multilingual models
- Experience in low-latency environments
Compensation
Competitive salary with performance incentives
Work Arrangement
Hybrid work model with flexible scheduling
Team
Collaborative team focused on AI-driven product improvements
About the Role
This position focuses on building intelligent systems that power search and personalized content delivery. The engineer will work on end-to-end ML solutions from concept to deployment, ensuring high accuracy and responsiveness.
What We Value
Technical excellence, curiosity, and a collaborative mindset are essential. We value candidates who take initiative, communicate clearly, and are committed to continuous learning in fast-evolving AI fields.
Available for qualified candidates
