Description

Responsibilities

• Develop and deploy recommendation, ranking, targeting, and personalization models using techniques such as collaborative filtering, embeddings, neural networks, and learning-to-rank.
• Process large-scale datasets and support batch and real-time model inference.
• Partner with engineering, product, analytics, and business teams to integrate ML solutions into production applications and data pipelines.
• Establish model evaluation frameworks, conduct A/B testing, and optimize performance using technical metrics and business KPIs.
• Explore advanced approaches, including contextual bandits, reinforcement learning, LLMs, and agentic AI, for potential personalization applications.

Qualifications

• Required
  • 5+ years of professional experience in machine learning, data science, or ML engineering, including meaningful recommendation or personalization experience, within e-commerce, retail, digital media, consumer technology, marketing technology, or another high-volume consumer environment.
  • Experience with customer segmentation, audience targeting, marketing analytics, or customer data platforms.
  • Proven experience building and operating production recommendation, ranking, targeting, or next-best-action models.
  • Strong Python skills and experience with PyTorch, TensorFlow, or comparable ML frameworks.
  • Strong understanding of recommendation algorithms, embeddings, ranking models, and large-scale behavioral or transactional data.
  • Experience deploying ML workloads in cloud environments, with hands-on AWS and Databricks experience.
  • Familiarity with modern LLM architectures and agentic AI frameworks.
  • Previous experience building recommender systems within the Marketing and/or Retail industries

Key Skills

Education

Bachelor's degree