Product ML Engineer
Tasks
- Build personalized product feeds and carousels
- Build production recommendation systems
- Build scalable inference services and ML APIs
- Collaborate with data platform on behavioral and transactional data
- Create next best action models
- Define offline and online ML metrics
- Design and run A/B tests
- Design candidate generation and retrieval
- Develop demand and product level forecasting models
- Develop personalization models
- Implement ranking and reranking
- Improve feature pipelines and training workflows
- Integrate recommendations with search and conversational shopping
- Monitor model performance and reliability
- Translate product problems into measurable ML problems
Perks/Benefits
Skills/Tech-stack
A/B | A/B Testing | B testing | CI/CD | Candidate Generation | Collaborative Filtering | Data Pipelines | Embeddings | Experimentation | Feature Engineering | Inference services | Learning-to-Rank | MLOps | Machine Learning | Machine Learning APIs | Model Monitoring | Observability | Personalization | Python | Ranking | Recommendation Systems | Retrieval | SQL | Series forecasting | Time Series | Time Series Forecasting
Education
N/A
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