Machine Learning Engineer Graduate (Global E-Commerce, Recommendation) - 2026 Start (PhD)
Tasks
- Build debugging tools
- Build feature engineering pipelines
- Build recommendation algorithms and systems
- Deploy machine learning models to production platforms
- Design predictive models for candidate generation and ranking
- Develop real-time data pipelines
- Develop user interest models
- Extract, transform, and load unstructured data
- Identify and resolve model and pipeline bugs
- Optimize and iterate on machine learning models
- Run model experiments and performance evaluation
- Support scalable production machine learning models
Perks/Benefits
- N/A
Skills/Tech-stack
Boosting trees | Bug Fixing | C++ | Collaborative Filtering | Data Pipelines | Data Processing | Deep learning | Experimentation | Factorization machines | Feature Engineering | Gradient Boosting Trees | Gradient boosting | Information Retrieval | Language Processing | Logistic Regression | Machine Learning | Matrix Factorization | Model Optimization | Natural Language | Natural Language Processing | PyTorch | Python | Real Time | Real-time Data | Real-time Data Processing | Recommendation Systems | TensorFlow | Wide and Deep | Word2Vec
Education
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