Senior Research Engineer - Applied AI/ML
Tasks
- Apply academic research to practical product applications
- Build maintain and optimize ETL and data pipelines for ML and analytics
- Collaborate on data architecture warehousing and pipeline scaling
- Conduct A B testing and causal inference for experiments
- Design and build AI driven features for search personalization pricing recommendations and fraud detection
- Design and implement ML models for personalization demand forecasting route optimization pricing anomaly detection and recommendations
- Develop ML pipelines and scalable infrastructure for model training and deployment
- Manage ML lifecycle including feature engineering training deployment monitoring and retraining
- Perform statistical analysis for product strategy
- Translate business requirements into models and production systems
Perks/Benefits
Skills/Tech-stack
A/B | A/B Testing | AWS | Amazon SageMaker | Apache Airflow | Apache Hadoop | Apache Kafka | Apache Spark | B testing | Causal Inference | ClickHouse | DBT | Deep learning | ETL | Feature Engineering | Google Cloud | Kubeflow | MLflow | Machine Learning | Microsoft Azure | Model Monitoring | NumPy | Pandas | Presto | PyTorch | Python | SQL | SciPy | Scikit-learn | TensorFlow
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