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- Tasks: Develop and implement machine learning models to enhance pricing strategies for hotels.
- Company: Leading hospitality tech provider focused on innovation and data-driven solutions.
- Benefits: Remote work, competitive salary, and opportunities for professional growth.
- Why this job: Make a real impact in the hospitality industry with cutting-edge AI technology.
- Qualifications: Experience in MLOps and strong collaboration skills required.
- Other info: Enjoy weekly travel while working in a dynamic and innovative environment.
The predicted salary is between 36000 - 60000 £ per year.
A leading hospitality technology provider is seeking a Machine Learning Ops Engineer to enhance data-driven pricing strategies for hotel customers. In this remote role, you will be responsible for developing and implementing robust machine learning models, ensuring system reliability, and collaborating with engineering teams.
You will bring your expertise in MLOps to optimize performance and contribute to innovative AI-driven solutions, making a significant impact on the future of hospitality.
MLOps Engineer — Remote with Weekly Travel (Pricing AI) in London employer: Cloudbeds
Contact Detail:
Cloudbeds Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land MLOps Engineer — Remote with Weekly Travel (Pricing AI) in London
✨Tip Number 1
Network like a pro! Reach out to folks in the hospitality tech space on LinkedIn or at industry events. We can’t stress enough how personal connections can open doors for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your MLOps projects and any innovative AI-driven solutions you've worked on. This will help us see your expertise in action.
✨Tip Number 3
Prepare for those interviews! Brush up on your machine learning models and system reliability concepts. We want to see how you think and solve problems, so be ready to discuss your thought process.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who take that extra step to connect with us directly.
We think you need these skills to ace MLOps Engineer — Remote with Weekly Travel (Pricing AI) in London
Some tips for your application 🫡
Show Off Your MLOps Skills: When you're writing your application, make sure to highlight your experience with machine learning models and MLOps. We want to see how you've optimised performance in past roles, so don’t hold back on the details!
Tailor Your Application: Take a moment to customise your application for this role. Mention how your skills align with enhancing data-driven pricing strategies specifically for the hospitality sector. It shows us you’re genuinely interested and have done your homework!
Be Clear and Concise: Keep your application straightforward and to the point. We appreciate clarity, so avoid jargon unless it’s relevant. Make it easy for us to see why you’d be a great fit for the team!
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it’s super easy to do!
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. Be ready to discuss specific tools and frameworks you've used, like TensorFlow or Kubernetes, and how they relate to optimising machine learning models in a production environment.
✨Showcase Your Problem-Solving Skills
Prepare to share examples of challenges you've faced in previous roles and how you tackled them. This could involve discussing how you improved system reliability or enhanced model performance, which is crucial for the hospitality tech sector.
✨Understand the Hospitality Industry
Familiarise yourself with the hospitality industry and its unique pricing strategies. Being able to discuss how AI can transform pricing for hotels will show that you're not just an MLOps Engineer, but someone who understands the business impact of your work.
✨Ask Insightful Questions
Prepare thoughtful questions about the company's current projects and future goals. This shows your genuine interest in the role and helps you gauge if the company aligns with your career aspirations, especially regarding innovation in AI-driven solutions.
