Royal Caribbean Cruises Ltd-posted about 22 hours ago
Full-time • Mid Level
Onsite • Miami, FL
5,001-10,000 employees

The ML Engineering team at Royal Caribbean Group is responsible for architecting the productionalized solution around rules-based and AI/ML models to integrate predictions seamlessly into the business processes, ensuring governance, resiliency, explainability, reproducibility, and scalability of the models. We are looking for a highly capable ML Platform Engineer to optimize rules-based and machine learning systems. As an engineer for the ML platform, you will be working at the intersection of machine learning, DevOps, and data engineering (i.e. MLOps).

  • Lead and consult with business stakeholders and data science teams to define data engineering and MLOps requirements.
  • Transforming business and data science prototypes and applying appropriate algorithms and tools.
  • Solving complex problems with multi-layered data sets, as well as optimizing existing machine learning libraries and frameworks.
  • Developing reusable data and feature stores for rules-based and AI/ML models.
  • Developing alerting tool frameworks for monitoring productionized model performance and effectiveness.
  • Automate deployments incorporating MLOps best practices into productionalized solutions.
  • Document frameworks and machine-learning processes.
  • Bachelor's degree in computer science, data science, mathematics, or a related field.
  • 5+ years of overall experience in Data Analytics.
  • 2+ years of experience with ML Engineering and/or ML Ops.
  • Experience building scalable machine learning systems and data-driven products working with cross-functional teams.
  • Well-developed software engineering fundamentals, including use of proper development, QA, and production environments, and the ability to write production-level code when needed.
  • Proficiency in Python and experience with common data analytics packages (e.g. Numpy, Pandas, Sklearn, PySpark).
  • Proficiency in SQL.
  • Good communication skills and the ability to understand and synthesize requirements across multiple project domains.
  • Works effectively with cross-functional teams.
  • Masters or PhD degree in computer science, data science, mathematics, or a related field.
  • Experience with Agile Software Development.
  • Experience in a large corporation or consulting firm with focus in marketing strategies, modeling, CRM and management sciences/statistics highly desired.
  • Familiarity with frameworks and languages designed for big-data analytics, including Spark and Azure Data Factory.
  • Experience with MLOps and ML experiment tracking tools, such as Azure DevOps and MLFlow or similar.
  • Experience with cloud computing frameworks or APIs, such as Microsoft Azure, Amazon Web Services and/or Google Cloud Platform
  • Familiarity with different data science techniques: statistics, machine learning, or cognitive AI.
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