O pozici
What Makes Us Unique
At Cloudbeds, we're not just building software, we’re transforming hospitality. Our intelligently designed platform powers properties across 150 countries, processing billions in bookings annually. From independent properties to hotel groups, we help hoteliers transform operations and uplevel their commercial strategy through a unified platform that integrates with hundreds of partners. And we do it with a completely remote team. Imagine working alongside global innovators to build AI-powered solutions that solve hoteliers' biggest challenges. Since our founding in 2012, we've become the World's Best Hotel PMS Solutions Provider and landed on Deloitte's Technology Fast 500 again in 2024 but we're just getting started.
Co budeš dělat
- As a Principal Machine Learning Engineer , you will play a key role in building and implementing features that empower lodging customers to make data-driven pricing decisions. Some of these features will use simple heuristic data, while others will leverage advanced machine learning techniques to optimize revenue strategies.
- You’ll work closely with product and engineering teams to identify opportunities for improvement, develop innovative solutions, and drive revenue growth for the hotels that rely on our platform.
- Your impact will be focused on ensuring the reliability, scalability, and high quality of our ML systems from development to production.
- You’ll be instrumental in establishing robust ML practices and rigorous testing processes across the entire ML lifecycle.
- From structuring data pipelines to implementing and validating ML models, you’ll own the end-to-end development of our revenue management application—ensuring hotels have the reliable, accurate insights they need to maximize their success.
Koho hledáme
- Architectural Expertise: Proven track record in designing, deploying, and maintaining production-grade, distributed ML systems.
- Deep MLOps Proficiency: Expert-level knowledge of CI/CD, orchestration (e.g., Apache Airflow, Prefect, Dagster), and model monitoring/drift detection at scale.
- Software Engineering Rigor: Strong background in Python, distributed systems, and backend development, with a firm grasp of software engineering best practices.
- Technical Strategy: Experience defining SLIs/SLOs and managing large-scale technical roadmaps.
- Leadership: Demonstrated ability to influence cross-functional teams, mentor junior talent, and drive consensus on complex technical decisions.
- Domain Knowledge : Ability to apply statistical and ML methods to optimize revenue management and pricing strategies.
- 5+ years of experience in a machine learning role, with demonstrated success in ML Engineering and deploying models to production.
- Proven expertise in designing and implementing ML testing strategies (e.g., data validation, model correctness, performance testing).
- Great understanding of machine learning principles (experimental design, statistical distributions and test, machine learning algorithms)
- Expertise in deploying ML models at scale on AWS, with experience using MLFlow or similar platforms.
- Strong Python programming skills and adherence to software engineering best practices (e.g., clean code, version control, code reviews).
- Expert-level SQL skills and experience working with large datasets for analysis and modeling.
- Strong problem-solving skills with the ability to apply creative, data-driven solutions to complex business challenges.
- Excellent communication and collaboration skills, with experience working cross-functionally with product and engineering teams.
- Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative field.
Benefity
- Remote First, Remote Always
- PTO in accordance with local labor requirements
- Monthly Wellness Fridays - enjoy an extra long weekend every month
- Full Paid Parental Leave
- Home office stipend based on country of residency
- Professional development courses in Cloudbeds University
- Access to professional development, including manager training, upskilling and knowledge transfer
