MLOps Engineer in City of Westminster

MLOps Engineer in City of Westminster

City of Westminster Full-Time 36000 - 60000 ÂŁ / year (est.) No home office possible
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At a Glance

  • Tasks: Build and implement AI-powered features to optimise hotel revenue strategies.
  • Company: Join Cloudbeds, a leader in transforming hospitality with innovative tech solutions.
  • Benefits: Enjoy remote work, competitive pay, wellness Fridays, and professional development opportunities.
  • Why this job: Make a real impact in the hospitality industry using cutting-edge machine learning technologies.
  • Qualifications: 3+ years in data engineering or machine learning, strong Python and SQL skills required.
  • Other info: Collaborative team culture with excellent career growth and a commitment to diversity.

The predicted salary is between 36000 - 60000 ÂŁ per year.

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.

MLOps Engineer in City of Westminster employer: Cloudbeds

At Cloudbeds, we pride ourselves on being a remote-first employer that champions innovation and collaboration in the hospitality tech space. Our inclusive work culture fosters continuous learning and professional development, offering employees opportunities to grow alongside industry leaders while enjoying benefits like monthly wellness Fridays and full paid parental leave. Join us in transforming hospitality with cutting-edge AI solutions, all from the comfort of your home, with occasional travel to our Paddington office for team synergy.
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Contact Detail:

Cloudbeds Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land MLOps Engineer in City of Westminster

✨Tip Number 1

Network like a pro! Reach out to folks in the industry, especially those already at Cloudbeds. A friendly chat can open doors and give you insider info on what it’s really like to work there.

✨Tip Number 2

Show off your skills! If you’ve got a portfolio or GitHub with projects related to MLOps, make sure to highlight them during interviews. It’s a great way to demonstrate your hands-on experience and passion for the field.

✨Tip Number 3

Prepare for technical challenges! Brush up on your Python and SQL skills, and be ready to tackle some coding problems. Cloudbeds loves candidates who can think on their feet and solve real-world issues.

✨Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, you’ll get all the latest updates about the role and company directly from us.

We think you need these skills to ace MLOps Engineer in City of Westminster

Machine Learning Operations (MLOps)
Data Engineering
Model Deployment
CI/CD for ML Pipelines
Apache Airflow
Python Programming
SQL
Data Pipeline Development
Model Performance Monitoring
Statistical Validation
A/B Testing
Collaboration Skills
Problem-Solving Skills
Software Quality Assurance

Some tips for your application 🫡

Tailor Your Application: Make sure to customise your CV and cover letter for the MLOps Engineer role. Highlight your experience with machine learning, data pipelines, and any relevant tools like Apache Airflow. We want to see how your skills align with our mission to transform hospitality!

Showcase Your Projects: Include specific examples of projects you've worked on that demonstrate your expertise in MLOps and model deployment. Whether it's a personal project or something from your previous job, we love seeing real-world applications of your skills!

Be Clear and Concise: When writing your application, keep it clear and to the point. Use bullet points where possible to make it easy for us to read through your qualifications. Remember, we’re looking for clarity in communication just as much as technical skills!

Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re serious about joining our remote team of innovators!

How to prepare for a job interview at Cloudbeds

✨Know Your MLOps Inside Out

Make sure you brush up on your MLOps knowledge before the interview. Understand the end-to-end machine learning lifecycle, from data pipelines to model deployment. Be ready to discuss how you've implemented CI/CD practices in your previous roles.

✨Showcase Your Problem-Solving Skills

Prepare to share specific examples of how you've tackled complex challenges in your past projects. Highlight your creative, data-driven solutions and how they led to improved outcomes. This will demonstrate your ability to think critically and innovate.

✨Familiarise Yourself with Their Tech Stack

Cloudbeds uses various tools like Apache Airflow for orchestration and AWS for deployment. Make sure you’re comfortable discussing these technologies and any relevant experience you have. It shows you're proactive and genuinely interested in the role.

✨Communicate Effectively

Since collaboration is key at Cloudbeds, practice articulating your thoughts clearly. Be prepared to explain technical concepts in a way that non-technical team members can understand. Good communication can set you apart from other candidates.

MLOps Engineer in City of Westminster
Cloudbeds
Location: City of Westminster

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