AI/ML Engineer

Own and improve the end-to-end recommendation system impacting millions of customers on app, website, and physical stores.

Enhance ranking quality by combining multiple data signals including facial compatibility, user interaction, store inventory, and bestsellers with a generative AI re-ranking layer.

Ensure platform reliability, low latency, and scalability by managing model, API, and infrastructure layers across the pipeline.

4+ years of experience building and deploying ML-powered production systems, with at least 2 years in recommendation, ranking, or search systems.

Demonstrated end-to-end ownership of ML systems from problem framing to deployment and monitoring.

Strong experience in recommender systems techniques and computer vision (face detection etc.) using PyTorch or TensorFlow.

Bachelor’s or Master’s degree in Computer Science, Engineering, Statistics or related field, or equivalent practical experience.

Engineer with hands-on experience integrating LLMs into production with focus on prompt design, evaluation, and latency/cost control.

Experienced in AWS services including Personalize, SageMaker, containerization (Docker, Kubernetes) and backend engineering with Python for scalable REST APIs.

Familiar with retail or omnichannel commerce domain, especially store-level inventory challenges and advanced ranking or exploration techniques.