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- Tasks: Design and oversee automated AI/ML pipelines for a leading health and fitness app.
- Company: Join a top health and fitness app in London with a focus on innovation.
- Benefits: Enjoy a competitive salary, flexible working conditions, and health benefits.
- Why this job: Make a real impact in the health sector by building scalable AI solutions.
- Qualifications: 7+ years of experience in AI/ML, strong Python skills, and cloud platform knowledge.
- Other info: Be part of a dynamic team with opportunities for growth and development.
The predicted salary is between 48000 - 72000 £ per year.
A leading health and fitness app in London is seeking a seasoned AI/ML Engineer to oversee the end-to-end AI/ML pipeline. You will design automated pipelines, implement CI/CD practices, and build infrastructure for AI applications.
Ideal candidates should have:
- Over 7 years of experience
- Strong expertise in Python
- Familiarity with cloud platforms like AWS or Azure
The role offers a competitive salary, flexible working conditions, and various health benefits.
MLOps Engineer — Build Scalable AI Pipelines employer: ETTravel
Contact Detail:
ETTravel Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land MLOps Engineer — Build Scalable AI Pipelines
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with other MLOps Engineers. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI/ML projects, especially those involving scalable pipelines. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge. Be ready to discuss your experience with CI/CD practices and cloud platforms like AWS or Azure. We want to see that you can walk the talk!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take the initiative to engage with us directly.
We think you need these skills to ace MLOps Engineer — Build Scalable AI Pipelines
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with AI/ML pipelines and CI/CD practices. We want to see how your skills in Python and cloud platforms like AWS or Azure make you the perfect fit for this role.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Tell us why you're passionate about health and fitness tech and how your background aligns with our mission. Keep it engaging and personal!
Showcase Relevant Projects: If you've worked on any projects that involved building scalable AI pipelines, don’t hold back! Share specific examples that demonstrate your expertise and problem-solving skills in the field.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at ETTravel
✨Know Your Tech Inside Out
Make sure you brush up on your Python skills and any relevant cloud platforms like AWS or Azure. Be ready to discuss specific projects where you've implemented CI/CD practices and designed automated pipelines. The more detailed examples you can provide, the better!
✨Showcase Your Problem-Solving Skills
Prepare to tackle hypothetical scenarios during the interview. Think about challenges you've faced in previous roles and how you overcame them. This will demonstrate your ability to think critically and adapt in a fast-paced environment.
✨Understand the Company’s Mission
Research the health and fitness app thoroughly. Understand their goals and how your role as an MLOps Engineer fits into their vision. This shows genuine interest and helps you tailor your answers to align with their objectives.
✨Ask Insightful Questions
Prepare a few thoughtful questions to ask at the end of the interview. Inquire about their current AI/ML projects or how they measure success in this role. This not only shows your enthusiasm but also helps you gauge if the company is the right fit for you.
