remote
Machine Learning Engineer - Kogan
ML Engineer
Design, build, and deploy machine learning models and data pipelines that power recommendation, forecasting, and fraud detection across eCommerce functions, using Python, cloud services, and containerization.
About the role
Key Responsibilities
- Develop, train, and productionize ML models for recommendation systems, demand forecasting, customer segmentation, churn prediction, pricing optimization, and fraud detection.
- Design and maintain end‑to‑end data pipelines that ingest, clean, and transform data from marketing, purchasing, logistics, and finance sources.
- Collaborate with cross‑functional teams to translate business problems into scalable ML solutions and evaluate model performance.
- Implement CI/CD workflows using Docker and cloud services (AWS) to ensure reliable, repeatable model deployments.
- Monitor models in production, perform root‑cause analysis on drift or failures, and iterate improvements.
Requirements
- Strong proficiency in Python and experience with ML frameworks such as TensorFlow or PyTorch.
- Hands‑on experience building data pipelines and working with SQL databases.
- Familiarity with cloud platforms (AWS) and containerization tools (Docker) for scalable deployment.
- Solid understanding of statistical modeling, feature engineering, and model evaluation techniques.
- Ability to work autonomously in a fast‑moving environment and communicate technical concepts to non‑technical stakeholders.
Skills
pythontensorflowpytorchsqlawsdocker