Machine Learning Engineer II
Tasks
- Analyze false negative and false positive datasets
- Build data pipelines
- Build model training and evaluation pipelines
- Debug data and system issues
- Design detection systems
- Develop rules and machine learning models
- Improve detection efficacy with new features
- Monitor false negative rates
- Perform feature engineering
- Train models on labeled datasets
Perks/Benefits
- N/A
Skills/Tech-stack
Algorithms | Computer Vision | Data Pipelines | Data analytics | Entity recognition | Feature Engineering | Machine Learning | Model Evaluation | Model Training | NLP | NumPy | Optimization | Pandas | PyTorch | Python | Recommendation Systems | SQL | Scikit-learn | Spark | TensorFlow | Text Understanding
Education
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