Founding Machine Learning Engineer
San Francisco, California
USD 190K-250K (estimate) Mid-level Full Time
Tasks
- Build ETL and feature pipelines
- Build and validate credit risk models
- Calibrate and evaluate models offline and online
- Define interview and hiring process for future ML hires
- Deploy models to production systems
- Design data pipeline for model training
- Detect model drift
- Develop training datasets
- Explain model tradeoffs to non technical stakeholders
- Frame credit risk modeling problems
- Iterate on production models
- Monitor model performance
- Partner with product and engineering on risk decisions
- Perform feature engineering
- Serve model predictions via production services
- Set modeling and ML engineering direction
- Translate partner constraints into modeling decisions
- Tune hyperparameters
Perks/Benefits
- N/A
Skills/Tech-stack
APIs | Collections modeling | Credit Risk | Credit risk modeling | Data leakage | Distributed Systems | Drift Detection | EAD | ETL | Exposure Management | Feature Engineering | Fraud Detection | Hyperparameter Tuning | Jupyter | Jupyter Notebook | Kaggle | LGD | LLMs | Label Noise | LightGBM | Machine Learning | Model Evaluation | Model Monitoring | Model calibration | PD | Pandas | PyTorch | Python | Risk Modeling | SQL | Scikit-learn | Selection bias | Statistical modeling | Supervised Learning | TensorFlow | Underwriting | XGBoost
Education
Regions
Countries
States
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