Sr. ML Engineer – ML & Applied AI

About Gap Inc.

At Gap Inc., we create culture as much as we create clothes. Our ambition is to become a high-performing house of iconic American brands that shape culture.

Our portfolio—Old Navy, Gap, Banana Republic, and Athleta—each brings a distinct point of view to how we show up in the world and serve our customers.

Old Navy democratizes style with quality and value for all. Gap champions originality through essential pieces that celebrate individuality. Banana Republic is rooted in a spirit of discovery, creating modern pieces inspired by craftsmanship and travel. Athleta champions the Power of She through confidence, strength, and movement.

We’re driven by a shared purpose: to bridge gaps—between people, perspectives, and possibilities—to create a better world.

We’re building a team that performs at a high level—people who think boldly, take ownership, and turn ideas into impact. If you’re ready to learn fast and help shape what’s next, you’ll fit right in.

About the Role

Gap Inc. is seeking a Senior Machine Learning Engineer with 10+ years of experience to design, build, and scale production-grade machine learning and AI systems that power data-driven decision making across the enterprise.

This role is focused on end-to-end ML system ownership, including data pipelines, feature engineering, model training, deployment, monitoring, and continuous optimization. You will lead the development of scalable ML platforms, drive best practices in MLOps, and enable reliable, high-performance model inference in both batch and real-time environments.

The ideal candidate combines strong software engineering expertise with deep ML knowledge and has experience building robust, scalable ML systems in production, including modern applications involving large language models (LLMs) and agent-based AI systems.

What You'll Do

• Architect and build scalable, production-grade ML systems from experimentation to deployment and lifecycle management
• Design and implement end-to-end ML pipelines, including data ingestion, feature engineering, training, validation, and inference
• Develop and maintain high-performance model serving systems using APIs (e.g., FastAPI) for real-time and batch inference
• Lead the design and implementation of feature stores and reusable feature pipelines across teams
• Build and optimize distributed data processing workflows using Spark, Databricks, or similar platforms
• Implement and enforce MLOps best practices, including CI/CD pipelines, automated retraining, model versioning, and experiment tracking
• Design and manage model monitoring and observability frameworks to track performance, drift, latency, and system health
• Drive strategies for model retraining, drift detection, and continuous improvement
• Collaborate closely with data engineers, platform teams, and product stakeholders to integrate ML solutions into production systems
• Contribute to the adoption of modern AI capabilities, including LLMs, vector databases, retrieval-augmented generation (RAG), and agentic workflows
• Ensure high standards of code quality, testing, documentation, and reproducibility

Who You Are

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field
• 10+ years of experience in machine learning, software engineering, or related roles, with significant experience in production ML systems
• Strong programming expertise in Python and solid software engineering fundamentals (data structures, system design, APIs)
• Extensive experience with ML frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow
• Proven experience designing and deploying scalable ML pipelines and services in production
• Hands-on experience with model serving frameworks and API development (e.g., FastAPI, Flask)
• Strong experience with containerization (Docker) and orchestration platforms such as Kubernetes
• Experience working with cloud platforms (GCP, AWS, or Azure) and building cloud-native ML solutions
• Deep understanding of ML lifecycle management, including training, evaluation, deployment, monitoring, and retraining
• Experience implementing CI/CD pipelines for ML workflows and managing version control systems (Git)
• Strong experience with SQL and distributed data processing frameworks (e.g., Spark, PySpark)
• Excellent problem-solving skills and ability to design scalable, maintainable systems

Benefits at Gap Inc.

• Merchandise discount for our brands: 50% off regular-priced merchandise at Old Navy, Gap, Banana Republic and Athleta, and 30% off at Outlet for all employees.
• One of the most competitive Paid Time Off plans in the industry.*
• Employees can take up to five “on the clock” hours each month to volunteer at a charity of their choice.*
• Extensive 401(k) plan with company matching for contributions up to four percent of an employee’s base pay.*
• Employee stock purchase plan.*
• Medical, dental, vision and life insurance.*
• See more of the benefits we offer.

*For eligible employees