Director, Machine Learning Engineering/MLOps

Hyatt - Chicago, IL

Full-time

Chicago, IL

Accommodation

About the position

Hyatt is seeking a highly skilled Machine Learning Engineer to develop algorithmic assets and features that enhance the guest experience and improve operational efficiencies. This role involves managing the ML platform, mentoring team members, and collaborating with data scientists to implement impactful ML solutions.

Responsibilities

• Own and refine the ML Platform supporting operational AI services and core ML infrastructure.
• Mentor and coach team members on best practices, code quality, design patterns, testing, debugging, and documentation.
• Hire, onboard, and retain top talent for the team, fostering a culture of innovation and collaboration.
• Foster a culture of quality through code reviews, design discussions, and best-practice implementation.
• Design and implement tools that streamline the entire ML workflow for rapid development and deployment of ML solutions.
• Partner with data scientists to design workflows and architectures that activate ML models and maximize their impact.
• Implement prototype solutions of algorithmic products using appropriate AWS services, considering scale and latency.
• Productionize final solutions via infrastructure-as-code patterns.
• Implement data processing workflows to enhance the Feature Store with impactful data, including data cleansing and imputation logic.
• Enhance existing algorithmic product architecture and workflows as needed.
• Collaborate with the data engineering team to ensure data science needs are met in the required format and cadence.
• Stay updated with the latest design patterns and AWS services related to Machine Learning Engineering.
• Partner with data architecture, governance, and security teams to ensure solutions meet required standards.

Requirements

• Master's degree in computer science, statistics, or related fields required; PhD preferred.
• 7+ years of data science experience focusing on ML platform and AI service development, with a proven track record of driving measurable business impact.
• Expertise in Python, SQL, and Spark; additional software experience preferred (e.g., Docker).
• Expertise in a broad array of machine learning frameworks (Scikit-Learn, XGBoost, Tensorflow, PyTorch, MXNet, etc.).
• Expertise in MLOps/LLMOps principles for the production of ML models (training, validation, deployment, monitoring).
• Experience managing multiple ML and AI services, including people management and hands-on implementation.
• Experience operating on AWS with large datasets and streaming data architectures.
• Experience in an Agile Methodology environment and familiarity with DevOps and CI/CD concepts.
• Excellent communication and teamwork skills.