Jobs → Engineering → Machine Learning Engineer

About the Role We are seeking a Machine Learning Engineer for a long-term contract position in Morristown, NJ. This role involves developing and deploying recommendation, ranking, targeting, and personalization models using advanced techniques such as collaborative filtering, embeddings, neural networks, and learning-to-rank. Key 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. Requirements • 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.