Senior Engineer, MLOps

Royal Caribbean Cruises Ltd • Miami, FL

48d • Onsite

About The Position

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).

Requirements

• 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.

Nice To Haves

• 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.

Responsibilities

• 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees