Company: Universal Parks & Resorts

Location: Orlando, FL

Expected salary:

Job date: Sun, 13 Jul 2025 07:02:56 GMT

Job description:

Job Description: Machine Learning Infrastructure Engineer

We are seeking a skilled Machine Learning Infrastructure Engineer to join our dynamic Digital & Technology Teams. In this role, you will be responsible for establishing scalable machine learning infrastructures, data pipelines, and robust deployment frameworks to support our innovative projects.

Key Responsibilities:

• Infrastructure Development: Design and implement scalable machine learning infrastructures that can handle large datasets and complex models.

• Data Pipeline Management: Create and optimize automated data pipelines to ensure the efficient flow of data for machine learning processes.

• Deployment Frameworks: Develop robust systems for deploying machine learning models into production, ensuring reliability and performance.

• Collaboration: Work closely with cross-functional teams, including Product, Marketing, and Engineering, to align ML solutions with business objectives.

• Stakeholder Engagement: Engage with enterprise stakeholders, including senior leadership and partners, to understand needs and present findings and recommendations.

• Continuous Improvement: Stay updated with the latest trends in machine learning and data engineering, implementing best practices for process improvements and scalability.

Qualifications:

• Bachelor’s degree in Computer Science, Data Science, or a related field.
• Proven experience in building machine learning infrastructures and data pipelines.
• Proficiency in programming languages (e.g., Python, Java) and ML frameworks (e.g., TensorFlow, PyTorch).
• Strong understanding of cloud platforms (e.g., AWS, Azure, GCP) and deployment tools (e.g., Docker, Kubernetes).
• Excellent communication and collaboration skills, with the ability to present technical concepts to non-technical stakeholders.

Join us to leverage cutting-edge technology and make impactful contributions to our data-driven initiatives!