You design, productionize, and maintain scalable machine learning services. You build full-lifecycle ML pipelines, develop recommendation and classification models, optimize training and inference performance, create reusable AI components, and apply software, data engineering, and MLOps best practices.
Responsibilities
- Develop and maintain production machine learning pipelines
- Adapt global frameworks for localized requirements
- Design and productionize recommendation models
- Design and productionize classification models
- Integrate models into merchant-facing products
- Optimize training and inference performance
- Develop reusable AI components
- Apply software and data engineering best practices
- Partner with MLOps and platform departments
- Lead projects from ideation to deployment
- Translate technical outcomes into clear insights
Requirements
- 4+ years of machine learning experience
- Expert-level Python
- PyTorch
- TensorFlow
- XGBoost or LightGBM
- Pandas
- Scikit-learn
- Spark
- SQL or Trino
- MLOps
- Kubernetes
- Docker
- Airflow
- Argo Workflows
- Prometheus
- Grafana
- Statistics
- Machine learning techniques
- Technical leadership
- Distributed GPU compute
- Machine learning feature stores