Senior Research Engineer - Applied AI/ML
Tasks
- Build ETL and data pipelines
- Collaborate on data architecture and warehousing
- Conduct causal inference for experiments
- Design and build ML features
- Develop ML models for personalization demand forecasting route optimization pricing anomaly detection recommendations
- Develop data pipelines and infrastructure
- Manage ML lifecycle data collection feature engineering training deployment monitoring retraining
- Perform statistical analysis and A/B testing
- Read and adapt research papers for product applications
- Translate business requirements into production systems
Perks/Benefits
Skills/Tech-stack
A/B | A/B Testing | AWS | Airflow | Apache Kafka | Apache Spark | Azure | B testing | Causal Inference | ClickHouse | DBT | Deep learning | ETL | Feature Engineering | GCP | Hadoop | Kubeflow | MLflow | Machine Learning | Model Monitoring | NumPy | Pandas | Presto | PyTorch | Python | Retraining | SQL | SageMaker | SciPy | Scikit-learn | TensorFlow
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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