About the Role
Design, build, and maintain machine learning models that enhance search relevance and user experience across a high-traffic digital marketplace platform.
Responsibilities
- Lead the architecture and implementation of machine learning pipelines for search ranking
- Collaborate with data scientists and engineers to improve query understanding and result relevance
- Optimize large-scale models for low-latency inference in production environments
- Define and track key performance metrics for search quality and user engagement
- Mentor senior engineers and contribute to technical strategy across teams
- Integrate structured and unstructured data sources to enhance search capabilities
- Drive experimentation frameworks to validate model improvements
- Ensure models are scalable, maintainable, and aligned with business goals
- Work closely with product teams to align ML capabilities with user needs
- Evaluate and adopt new ML frameworks and technologies
- Troubleshoot and resolve production issues related to search ranking
- Contribute to data labeling and annotation strategies for training sets
- Develop semantic matching techniques for queries and listings
- Implement personalization features within search results
- Maintain documentation and promote best practices in ML engineering
- Lead code reviews and ensure high standards in software quality
- Design A/B tests to measure impact of algorithmic changes
- Ensure compliance with data privacy and platform policies
- Support deployment automation and monitoring for ML services
- Collaborate on cross-team initiatives to unify search experiences
- Research and prototype next-generation search technologies
- Balance precision, recall, and diversity in search output
- Optimize for multilingual and regional search behavior
- Work with infrastructure teams to improve model serving efficiency
- Drive initiatives to reduce technical debt in ML systems
Compensation
Competitive salary and benefits package
Work Arrangement
Hybrid work model with flexibility
Team
Part of the core search infrastructure team focused on scalable machine learning systems
Why This Role Matters
- Search is the primary interface for user discovery on the platform, making this role critical to overall user satisfaction and business success.
- You will shape the future of how millions of users find relevant listings through intelligent ranking and semantic understanding.
Technology Stack
- The team uses Python, Java, and Scala for ML and backend services.
- Models are deployed on Google Cloud Platform using Kubernetes and BigQuery.
- Primary tools include TensorFlow, scikit-learn, Airflow, and Elasticsearch.
Available for qualified candidates
