MLOps Engineer

Third-Party Job Posts; United Kingdom; Hybrid; GBP 80,000 - 100,000; Full time

Job summary

A leading hospitality solutions provider is seeking a Machine Learning Ops Engineer to develop features that help hoteliers optimize revenue through AI-driven insights. This role involves establishing MLOps practices and ensuring the reliability of ML systems. Candidates should have a Bachelor's degree in a relevant field and at least 3 years of experience in machine learning or data engineering. This fully remote position emphasizes collaboration among global teams, fostering innovation in the hospitality industry.

Benefits

PTO in accordance with local labor requirements

Monthly Wellness Fridays

Full Paid Parental Leave

Home office stipend

Professional development courses in Cloudbeds University

Qualifications

• 3+ years of experience in a data engineering or machine learning role.
• Experience with MLOps and deploying models to production.
• Expertise in ML testing strategies.

Responsibilities

• Develop and implement end-to-end machine learning features.
• Establish MLOps practices including CI/CD for model training.
• Collaborate with cross-functional teams to improve system performance.

Skills

Python programming

Data engineering

MLOps practices

SQL skills

Problem-solving skills

Communication and collaboration

Education

Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, or related field

Tools

Apache Airflow

AWS

MLFlow

Job description

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.

Location: Remote with expected travel into Paddington 2 days per week.

How You'll Make an Impact:

As a Machine Learning Ops 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 MLOps 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.

Our machine learning team is energized by the unique challenge of revolutionizing guest experiences through AI-driven insights, transforming traditional hospitality with cutting-edge predictive algorithms.

We thrive on collaborative innovation, where data scientists, engineers, and product experts seamlessly blend their expertise to prototype bold ideas and directly impact operational efficiency.

People who are passionate about continuous learning, unafraid to challenge conventions, and excited by the intersection of hospitality and deep technical prowess will find their home among our forward-thinking team.

What You Bring to the Team:

• Develop and implement end-to-end machine learning features that enable customers to optimize their revenue strategies, with a strong emphasis on production readiness and system reliability.
• Establish and maintain robust MLOps practices including CI/CD for model training, testing, deployment, and monitoring.
• Design, build, and maintain highly reliable and well-tested data and ML pipelines to extract, transform, and structure large datasets for ML applications.
• Expertise in using Apache Airflow (or similar orchestration tools like Prefect/Dagster) to define, schedule, and monitor complex data and ML workflows (DAGs).
• Implement comprehensive software quality and testing processes for ML systems, including unit, integration, and end-to-end testing for both code and data/model performance.
• Design, train, and rigorously test machine learning models where needed to improve pricing optimization, focusing on statistical validation and production stability.
• Implement model performance monitoring (e.g., drift detection, data quality checks) to ensure deployed models maintain accuracy and relevance over time.
• Collaborate cross-functionally with product, engineering, and data science teams to define SLIs/SLOs for ML services and improve system performance, stability, and usability.
• Conduct structured A/B testing and experimentation to validate model effectiveness and continuously improve performance, documenting results and sharing technical insights.

What Sets You Up for Success:

• Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative field.
• 3+ years of experience in a data engineering or machine learning role, with demonstrated success in MLOps and deploying models to production.
• Proven expertise in designing and implementing ML testing strategies (e.g., data validation, model correctness, performance testing).
• 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.

Bonus Skills to Stand Out (Optional):

• 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, Data Science, or a related field. Relevant certifications (AWS, MLFlow, or other data science/ML certifications).

What to Expect - Your Journey with Us

Behind Cloudbeds' revolutionary technology is a team of redefining what's possible in hospitality. We're 650+ employees across 40+ countries, bringing together elite engineers, AI architects, world-class designers, and hospitality veterans to solve challenges others haven't dared to tackle. Our diverse team speaks 30+ languages, but we all share one language: a passion for innovation and travel. From pioneering breakthroughs in machine learning to revolutionizing how hotels operate, we're not just watching the future of hospitality unfold – we're coding it, designing it, writing it and shipping it. If you're ready to work alongside some of the brightest minds in tech who are obsessed with using AI to transform a trillion-dollar industry, this is your chance to be part of something extraordinary.

• Overall 10 Best Places to Work | HotelTechAwards (2025)
• Top 10 People’s Choice(2024)
• 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.

Everyone is Welcome - A Culture of Inclusion

Cloudbeds is proud to be an Equal Opportunity Employer that celebrates the diversity in our global team! We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.

Cloudbeds is committed to the full inclusion of all qualified individuals. As part of this commitment, Cloudbeds will ensure that persons with disabilities are provided reasonable accommodations in the hiring process. We encourage deaf, hard of hearing, deaf-blind, and deaf-disabled individuals to apply. If reasonable accommodation is needed to participate in the job application or interview process or to perform essential job functions, please contact our HR team by phone at 858-201-7832 or via email at [e-mail] . Cloudbeds will provide an American Sign Language (ASL) interpreter where needed as a reasonable accommodation for the hiring processes.

Equal Employment Opportunity Information

For government reporting purposes, we ask candidates to respond to the below self-identification survey. Completion of the form is entirely voluntary. Whatever your decision, it will not be considered in the hiring process or thereafter. Any information that you do provide will be recorded and maintained in a confidential file. We do not discriminate on the basis of any protected group status under any applicable law. I f you choose to complete this survey, your responses may be used to identify areas of improvement in our hiring process.

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