Machine Learning Engineer Intern (Global E-Commerce, Recommendation) - 2027 Start (PhD)
Tasks
- Build ETL for real time unstructured data
- Build real-time data pipelines
- Build recommendation algorithms and systems
- Build user interest models
- Debug deployed model issues
- Design build and debug ML tools
- Develop candidate generation and ranking models
- Integrate models with deployment platforms
- Optimize and iterate predictive models
- Perform feature engineering
- Run model experiments and evaluate performance
- Support production deployment of scalable ML models
- Work on statistics scripting and programming
Perks/Benefits
Skills/Tech-stack
C++ | Collaborative Filtering | Data Mining | Data Pipelines | Deep Neural Networks | Deep learning | ETL | Experimentation | Factorization machines | Feature Engineering | Gradient boosting | Information Retrieval | Language Processing | Logistic Regression | Machine Learning | Matrix Factorization | Natural Language | Natural Language Processing | Neural Networks | Online Advertising | PyTorch | Python | Recommendation Systems | TensorFlow | Wide and Deep | Word2Vec
Education
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