Senior Machine Learning Engineer, Fraud Detection
Core
Lead the creation and deployment of scalable ML models to detect account sharing fraud using user behavior data like geolocation, concurrent sessions, and device profiles.
Role type
Senior Machine Learning Engineer (Fraud Detection)
Builds
Real-time anomaly detection systems for VOD streaming platforms
Domain
Streaming / Fraud Detection
Deliverable
production ML models
Required skills
Python, TensorFlow, PyTorch, XGBoost, MLOps (MLflow, Docker), Cloud Infrastructure (AWS, GCP), Anomaly Detection, Model Optimization, API Integration, A/B Testing
Preferred skills
Certifications in cloud ML
Technologies
AWS SageMaker, Databricks MLFlow, TensorFlow, PyTorch, XGBoost, MLflow, Docker, AWS, GCP
Responsibilities
Design and implement machine learning algorithms for real-time unauthorized account sharing detection; Develop end-to-end ML pipelines for data preprocessing, training, evaluation, and deployment; Optimize models for performance, scalability, and efficiency; Integrate ML solutions with existing systems via APIs and establish monitoring for model drift; Collaborate on A/B testing to refine algorithms.
Seniority
Senior, hands-on IC
