Lead, Machine Learning Operations Engineer

Royal Caribbean Cruises - Miami, FL

Full-time - Senior

Miami, FL

Administrative and Support Services

About the position

The Lead Machine Learning Operations Engineer at Royal Caribbean Group will be responsible for the implementation and iteration of AI/ML solutions, providing architectural guidance and development support. This role involves working closely with data scientists, data engineers, and business stakeholders to support various AI/ML projects while creating broader AI capabilities for the Data Science team, including Generative AI initiatives.

Responsibilities

• Drive new AI capabilities for the ML Platform including GenAI, OpenAI, DBRX, and Mosaic ML.
• Create a Center of Excellence to govern GenAI use cases, providing guidance and establishing best practices.
• Provide support and guidance to multiple Data Science projects.
• Build, maintain, and document reusable frameworks by enhancing existing Python packages and creating new ones.
• Automate CI/CD testing and deployments incorporating MLOps best practices.
• Implement monitoring capabilities for model performance and effectiveness in production.
• Maintain and enhance the internal Azure OpenAI website used across the company.

Requirements

• Master's or PhD degree in computer science, data science, mathematics, or a related field.
• Bachelor's degree in software engineering, computer science, data science, mathematics, or a related field.
• 7+ years of overall experience in Data Analytics & AI.
• 5+ years of experience with ML Engineering and/or ML Ops, with up to 2 years of Software Engineering experience counting towards this requirement.
• Sharp critical thinking skills and ability to learn and question complex processes and solutions.
• Well-developed software engineering skills, including use of proper development, QA, and production environments, object-oriented programming, version control, and knowledge of multiple programming languages.
• Experience creating proof of concepts and evaluating new tools and technologies to establish and document best practices.
• Experience building scalable machine learning systems and data-driven products working with cross-functional teams.
• Proficient in Python and experience with common data analytics packages (e.g. Numpy, Pandas, Sklearn, PySpark).
• Proficient in SQL.
• Experience serving containerized solutions in the cloud.
• Good communication skills and the ability to understand and synthesize requirements across multiple project domains.

Nice-to-haves

• Experience creating and maintaining Python packages.
• Experience with web development frameworks and languages (JavaScript, ReactJS, Flask, or others).
• Familiarity with frameworks and languages designed for big-data analytics, including Spark, Databricks, and Azure Data Factory.
• Experience with MLOps and ML experiment tracking tools, such as Azure DevOps and MLFlow or similar.
• Experience with cloud computing services such as Microsoft Azure, Amazon Web Services and/or Google Cloud Platform.
• Familiarity with different data science techniques: statistics, machine learning, or cognitive AI.

Benefits

• Competitive compensation and benefits package.
• Excellent career development opportunities.