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Cloudbeds
Cloudbeds

Staff ML Engineer

RemoteEUEurope
Published
Role
AI / ML
Experience
Staff
Company size
Mid-size
Salary not disclosed
Check eligibility

Open to Anywhere in EU & Europe. Set where you work from to check your eligibility.

No BS summary

Staff ML Engineer needed to build and implement features for data-driven pricing decisions using heuristics and advanced ML. Requires 5+ years of ML Engineering experience, strong Python, distributed systems, MLOps, AWS (Sagemaker, MLFlow), SQL, and experience defining SLIs/SLOs. Must be able to influence teams and mentor junior talent.

Core skills

PythonMachine LearningMLOps

Required skills

distributed systemsbackend developmentCI/CDorchestrationmodel monitoringdrift detectionAWSMLFlowSagemakerSQLDockerTerformKubernetesApache AirflowFlink

Optional skills

GitHub ActionsJenkinsAirflow DAG deploymentdata quality monitoring tools and frameworks

Required languages

English

What you'll do

  • Building and implementing features that empower lodging customers to make data-driven pricing decisions.
  • Leveraging advanced machine learning techniques to optimize revenue strategies.
  • Working 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.
  • Ensuring the reliability, scalability, and high quality of our ML systems from development to production.
  • Establishing robust ML practices and rigorous testing processes across the entire ML lifecycle.
  • Owning the end-to-end development of our revenue management application—ensuring hotels have the reliable, accurate insights they need to maximize their success.

What they require

  • Proven track record in designing, deploying, and maintaining production-grade, distributed ML systems (Sagemaker)
  • Expert-level knowledge of CI/CD, orchestration (e.g., Apache Airflow, Flink), and model monitoring/drift detection at scale.
  • Strong background in Python, distributed systems, and backend development, with a firm grasp of software engineering best practices.
  • Experience defining SLIs/SLOs and managing large-scale technical roadmaps.
  • Demonstrated ability to influence cross-functional teams, mentor junior talent, and drive consensus on complex technical decisions.
  • 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, Sagemaker or similar platforms.
  • Strong Python programming skills and adherence to software engineering best practices (e.g., clean code, version control, code reviews, using Docker, Terform, Kubernetes).
  • 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.
  • Experience with CI/CD tooling (e.g., GitHub Actions, Jenkins) specifically for ML pipelines and Airflow DAG deployment.
  • Experience with data quality monitoring tools and frameworks.
  • Master’s or PhD in Computer Science, Mathematics, or a related field.

Benefits

  • Remote First, Remote Always
  • PTO in accordance with local labor requirements
  • Monthly Wellness Fridays - enjoy an extra-long weekend every month
  • Fully 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
  • Everyone is Welcome - A Culture of Inclusion

Payment service for hotels, accounting and finance management

HospitalityMid-sizecloudbeds.com/

What people say about this company

3.2/ 5

Salary not disclosed