Related skills
sql python pytorch spark scikit-learn📋 Description
- Design, train, and deploy ML/LLM models to detect fraud across users, payments, and marketplace.
- Lead end-to-end architecture of fraud detection, prevention, and intervention systems.
- Build intelligent user graphs to model behavioral patterns and collusion networks.
- Develop scalable data pipelines and real-time inference for high-volume ML workloads.
- Conduct deep behavioral and adversarial analysis to uncover fraud trends.
- Partner with Trust & Safety, Payments, and Infrastructure to develop features and evaluation pipelines.
🎯 Requirements
- Bachelor’s degree in CS or related field, or equivalent.
- 2–6 years in ML or software engineering (risk/fraud).
- Python and ML libs: scikit-learn, PyTorch, LightGBM.
- Backend deployment of ML models to production.
- Experience with data analysis and ETL (SQL, Spark, DBT).
- Familiarity with fraud techniques and orchestration tools (Dagster, Kubeflow).
🎁 Benefits
- Generous Holiday and Time off Policy
- Health Insurance: Medical, Dental, Vision
- Work From Home Support + home-office allowance
- Monthly allowance for cell phone and internet
- Care benefits: wellness, childcare, family planning
- Retirement: 401(k) and pension plans
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