Senior Machine Learning Operations Engineer

Position Summary

The Machine Learning / MLOps Engineering team at Royal Caribbean Group is responsible for the successful implementation and iteration of AI / ML solutions including providing architectural guidance and development support.

Some of our focus areas include developing reusable frameworks, code optimization and refactoring, scaling up ML solutions, and foreseeing and testing for common issues that may arise in production.

We are looking for a highly capable Senior Machine Learning / MLOps Engineer with a strong Software Engineering and DevOps background.

As a Senior MLOps Engineer, you will be embedded and supporting a revenue generation or cost optimization project, ensuring its success in production by improving the code, creating automated CI / CD testing, and developing frameworks that can be reused for other similar projects.

Essential Duties and Responsibilities

• Build, maintain, and document machine learning frameworks (python packages) used across multiple projects.
• Support a project team with Data Scientists, Business Stakeholders, Analysts, and Data Engineers.
• Develop reusable feature stores for rules-based and AI / ML models.
• Implement monitoring capabilities for model performance and effectiveness in production.
• Automate CI / CD testing and deployments incorporating MLOps best practices.
• Perform other duties as required.
• This job description in no way states or implies that these are the only duties to be performed by the employee occupying this position.

Employees will be required to perform any other job-related duties assigned by their supervisor or management

Preferred Qualifications

• Master’s or PhD degree in computer science, data science, mathematics, or a related field.
• Experience with sensor data or other noisy data types.
• 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 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.

Minimum Qualifications, Knowledge, and Skills

• Bachelor's degree in software engineering, computer science, data science, mathematics, or a related field.
• 5+ years of overall experience in Data Analytics.
• 3+ years of experience with ML Engineering and / or ML Ops. Up to 2 years of Software Engineering or Data Engineering experience can also count towards this requirement.
• Sharp critical thinking skills and ability to learn and question complex processes and solutions.
• Experience building scalable machine learning systems and data-driven products working with cross-functional teams.
• Experience creating python packages
• 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.
• 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.
5 days ago