Machine Learning Engineer Graduate (Global E-Commerce, Recommendation) - 2027 Start
Tasks
- Build large-scale recommendation algorithms
- Build real-time data pipelines
- Collaborate with teams on statistics and programming
- Create debugging and supporting tools
- Deploy scalable machine learning models
- Design develop evaluate predictive ranking models
- Develop user interest models
- Identify and resolve production model issues
- Optimize and iterate machine learning models
- Perform feature engineering
- Run experiments to evaluate deployed models
- Transform and load realtime unstructured data
- Work with model deployment software platforms
Perks/Benefits
- N/A
Skills/Tech-stack
Boosting trees | C plus plus | Collaborative Filtering | Data Mining | Data Pipelines | Data Processing | Deep Neural Networks | Experiment design | Factorization machines | Feature Engineering | Gradient Boosting Trees | Gradient boosting | Information Retrieval | Language Processing | Logistic Regression | Machine Learning | Matrix Factorization | Natural Language | Natural Language Processing | Neural Networks | Predictive Modeling | PyTorch | Python | Real Time | Real-time Data | Real-time Data Processing | Recommendation Systems | TensorFlow | Wide and Deep | Word2Vec
Education
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