The Opportunity
Hyatt seeks an extraordinary ML Engineer to help build the algorithmic assets and features that Hyatt guests, members, customers, and internal users leverage to transform the guest experience and drive efficiencies across the operations of our business.
In this role, you will have the opportunity to lead a growing ML platform and MLE team that supports an array of data science products across Personalization, GenAI, Forecasting, and Decision Science.
You will be part of a ground-floor, hands-on, highly visible team which is positioned for growth and is highly collaborative and passionate about data science.
Applying the latest techniques and approaches across the domains of data science, machine learning, and AI isn’t just a nice to have, it’s a must. You will be part of a team passionate about diversity, equity, and inclusion, committed to nurturing curiosity and new skills and building connections with stakeholders, colleagues, and guests across the organization.
The Role
- Own and refine our ML Platform supporting operational AI services and core ML infrastructure such as Feature Store, Observability, MLOps, Data, etc.
- Mentor and coach your team members on best practices, code quality, design patterns, testing, debugging, and documentation.
- Hire, onboard, and retain top talent for your team and foster a culture of innovation, collaboration, and excellence.
- Foster a culture of quality through code reviews, design discussions, and best-practice implementation.
- Design and implement tools that streamline the entire ML workflow, enabling rapid development and deployment of impactful ML solutions.
- Partner with data scientists to design workflows/architectures that activate ML models and maximize their impact, such as real-time streaming use cases and offline batch optimizations.
- Implement prototype solutions of algorithmic products leveraging appropriate AWS services with consideration for scale and latency where applicable.
- Implement and productionize final solutions via infrastructure-as-code pattern.
- Implement data processing workflows to enhance our Feature Store with impactful data including appropriate data cleansing/imputation logic.
- Enhance existing algorithmic product architecture/workflow as needed to maximize the impact of the algorithmic product.
- Partner with data engineering team to ensure data science data needs are being delivered in the appropriate format/cadence required for maximum impact.
- Stay up to date with the latest design patterns and AWS services with respect to Machine Learning Engineering.
- Partner with data architecture, data governance, and security team to ensure solutions meet required standards.
Qualifications
- Master’s degree in computer science, statistics, or related fields required. PhD preferred.
- 7+ years of data science experience with a focus on ML platform and AI service development, with a history of successfully driving measurable business impact. Hospitality experience is not required.
- Expertise in Python, SQL, and Spark. Additional software experience preferred ie Docker.
- Expertise in a broad array of machine learning frameworks (Scikit-Learn, XGBoost, Tensorflow, PyTorch, MXNet, etc).
- Expertise in MLOps/LLMOps principles, enabling the production of ML models (training, validation, deployment, monitoring).
- Experience managing (accountable, responsible) multiple ML and AI services, including both people management and hands-on implementation.
- Experience operating on AWS with large datasets.
- Experience with streaming data architectures.
- Experience operating in an Agile Methodology environment.
- Experience with DevOps and CI/CD concepts.
- Excellent communication and teamwork skills.
The position responsibilities outlined above are in no way to be construed as all-encompassing. Other duties, responsibilities, and qualifications may be required and/or assigned as necessary.
We welcome you:
Research shows that women, people of color, and other historically excluded groups, tend to apply to jobs, only if they meet all the listed job qualifications. Unsure if you check every box, but feeling inspired to enhance your career? Apply. We’d love to consider your unique experiences and how you could make Hyatt even better.
