Senior Machine Learning Engineer

Design, develop, and improve production-grade machine learning models for enterprise order management use cases such as prediction, ranking, recommendation, and forecasting.

Own the end-to-end ML lifecycle from problem framing, data preparation, modeling, deployment, to monitoring and customer delivery support.

Collaborate cross-functionally with product, engineering, IT, and customer teams to ensure model reliability, reproducibility, and accountable AI practices in production environments.

Strong applied machine learning expertise with experience deploying models into production and measuring real-world performance.

Proficiency in Python and machine learning libraries (e.g., PyTorch, TensorFlow, scikit-learn), plus strong SQL skills for large relational datasets.

Bachelor's degree in Computer Science, Statistics, Mathematics, Engineering, or related technical field (or equivalent practical experience).

Work Experience Required: Not explicitly mentioned in the JD.

Experienced in handling large-scale, complex, and imperfect enterprise datasets and building reliable data and feature pipelines.

Comfortable working directly with customers and delivery teams in dynamic environments with varying requirements and data quality.

Familiarity with responsible AI practices, MLOps tools, containerized deployment (e.g., Kubernetes), and integration with broader product stacks using TypeScript or JavaScript.