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The Royal Caribbean Groups Machine Learning Engineering team has an exciting career opportunity for a full time Lead Machine Learning Operations Engineer reporting to the Manager of Machine Learning Engineering.
This position will work on-site in Miami or Miramar, Florida.
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 Lead Machine Learning Platform / MLOps Engineer with a strong Software Engineering and DevOps background. As a Lead MLOps Engineer, you will (1) be supporting many small to medium sized AI/ML projects partnering closely with data scientists, data engineers, and business stakeholders on the projects; and (2) have centralized responsibilities to create broader AI capabilities for the Data Science team including GenAI.
Essential Duties and Responsibilities
- Drive new AI capabilities for the ML Platform including: GenAI, OpenAI, DBRX, Mosaic ML and others.
- Create a Center of Excellence to govern GenAI use cases providing guidance, establishing best practices, and building out solutions.
- 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.
Preferred Qualifications
- Masters or PhD degree in computer science, data science, mathematics, or a related field.
- 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.
Minimum Qualifications, Knowledge, and Skills
- 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. Up to 2 years of Software Engineering experience can also count 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.
- Works effectively with cross-functional teams.
We know there's a lot to consider. As you go through the application process, our recruiters will be glad to provide guidance, and more relevant details to answer any additional questions. Thank you again for your interest in Royal Caribbean Group. We'll hope to see you onboard soon!