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Applied Machine Learning Scientist

OpenTable

Skills

Required

  • machine learning systems
  • machine learning metrics
  • data drift
  • overfitting
  • software engineering
  • algorithms
  • Python
  • PyTorch
  • TensorFlow
  • scikit-learn

Preferred

  • machine learning
  • multimodal
  • large language model
  • LLM workflows
  • image processing
  • search systems
  • information retrieval
  • learning-to-rank
  • text

Join OpenTable, a leading online restaurant reservation platform, as an Applied Machine Learning Scientist. In this role, you will prototype, evaluate, and productionize machine learning systems to enhance restaurant content understanding, retrieval, matching, ranking, and recommendation. You will also build and monitor scalable data and machine learning pipelines, design evaluation frameworks, and collaborate cross-functionally with engineering, product, and content teams. This position offers generous benefits, including parental leave, paid vacation, and mental health support.

Responsibilities

  • Prototyping, evaluating, and productionizing machine learning systems to enhance restaurant content understanding, retrieval, matching, ranking, and recommendation.
  • Building and monitoring scalable data and machine learning pipelines, ensuring strong data quality and reproducibility.
  • Collaborating cross-functionally with engineering, product, and content teams to translate ambiguous business needs into practical, scalable machine learning solutions.
  • Hands-on experience training, tuning, evaluating, and debugging classical machine learning and deep learning models, including Transformers

Requirements

  • Bachelor's, Master's, or PhD degree in Computer Science, Statistics, Mathematics, or a related technical field, with 0-3 years of relevant academic or professional experience
  • Demonstrated ability to translate business goals into machine learning metrics and address common production issues like data drift and overfitting
  • Strong foundation in software engineering principles, algorithms, and data structures, with familiarity in large-scale data systems
  • Proficiency in Python and foundational machine learning frameworks (e.g., PyTorch, TensorFlow, scikit-learn, XGBoost)
  • Experience with human-in-the-loop machine learning systems supporting operational or editorial workflows
  • Demonstrated applied curiosity through substantial technical projects, research, open-source contributions, or internships

Preferred

  • Experience applying machine learning to text, image, or multimodal content for retrieval, matching, ranking, or recommendation
  • Familiarity with large language model (LLM) workflows for text and image processing tasks
  • Exposure to search systems, information retrieval, embeddings, or learning-to-rank methodologies

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