Remote Production ML Engineer - Recommender Systems

Gap Inc; United States; Remote; USD 207,000 - 217,000; Full time

Job summary

Gap Inc. is seeking a data science professional to design, develop, and maintain production-scale distributed ML pipelines. You will work with PySpark, Databricks, Delta Lake, MLflow, and Unity Catalog to power e-commerce recommendations across brands and markets.

You will own full ML workflows, including data ingestion, feature engineering, model training, inference, versioning, and automated refreshes, while optimizing performance and cost in a remote US-based setting.

Qualifications

• Master's degree in DS/CS/CIS or related field with 4 years of experience.

Responsibilities

• Design, build, and maintain production-scale ML pipelines and end-to-end workflows.
• Implement DL models (transformers, embeddings, collaborative filtering) for recommender systems.
• Develop feature engineering frameworks combining multi-modal attributes and signals.
• Collaborate with Product Managers and cross-functional teams to translate requirements into designs.
• Build CI/CD and deployment automation using GitHub Actions and Databricks workflows.
• Establish data governance, validation, monitoring for quality, lineage, and compliance.

Skills

ML pipelines

Transformer models

Recommender systems

MLOps

Python

SQL

Education

Master's degree in Data Science/CS/CIS or related field

Tools

Azure Databricks

Apache Spark

Delta Lake

GitHub Actions

Job description

Gap Inc. is seeking a data science professional to design, develop, and maintain production-scale distributed ML pipelines. You will work with PySpark, Databricks, Delta Lake, MLflow, and Unity Catalog to power e-commerce recommendations across brands and markets.

You will own full ML workflows, including data ingestion, feature engineering, model training, inference, versioning, and automated refreshes, while optimizing performance and cost in a remote US-based setting.