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- Tasks: Build and improve reliable data pipelines for machine learning projects.
- Company: Dynamic tech company focused on MLOps and innovation.
- Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
- Why this job: Join a cutting-edge team and make a real impact in the world of data science.
- Qualifications: Experience in data engineering and MLOps practices.
- Other info: Exciting career prospects in a fast-paced environment.
The predicted salary is between 43200 - 72000 £ per year.
The following information provides an overview of the skills, qualities, and qualifications needed for this role.
Hybrid 2/3 days London Outside IR/35
We’re looking for a Data Engineer with strong MLOps ownership, someone who builds reliable data pipelines and designs, runs, and improves ML pipelines in production. You won’t be training models day-to-day like a Data Scientist; instead, you’ll enable Data Science by delivering high-quality datasets, reproducible training pipelines, robust deployment processes, and monitoring solutions.
MLOps Data Engineer (GCP) in London employer: Xcede
Contact Detail:
Xcede Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land MLOps Data Engineer (GCP) in London
✨Tip Number 1
Network like a pro! Reach out to folks in the MLOps community on LinkedIn or attend meetups. Building connections can lead to job opportunities that aren't even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data pipelines and ML projects. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for those interviews! Brush up on your technical knowledge and be ready to discuss your past projects. We recommend practicing common MLOps scenarios to demonstrate your problem-solving skills.
✨Tip Number 4
Apply through our website! We make it easy for you to find roles that match your skills. Plus, it shows you're genuinely interested in joining our team!
We think you need these skills to ace MLOps Data Engineer (GCP) in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with MLOps and data engineering. We want to see how you've built reliable data pipelines and improved ML pipelines in production, so don’t hold back on those details!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Tell us why you're passionate about MLOps and how your skills align with our needs. We love hearing about your unique experiences, so make it personal and engaging.
Showcase Relevant Projects: If you've worked on any projects that demonstrate your ability to deliver high-quality datasets or robust deployment processes, be sure to include them. We’re keen to see real-world examples of your work!
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 Xcede
✨Know Your MLOps Inside Out
Make sure you’re well-versed in MLOps principles and practices. Brush up on how to build and maintain reliable data pipelines, as well as the tools and technologies commonly used in GCP. Being able to discuss your experience with these will show that you’re ready to hit the ground running.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific challenges you've faced in previous roles and how you overcame them. Think about times when you improved ML pipelines or dealt with data quality issues. This will demonstrate your ownership and proactive approach to MLOps.
✨Familiarise Yourself with the Company’s Tech Stack
Research the specific tools and technologies the company uses for their MLOps processes. If they mention using certain GCP services, make sure you understand how they work and can discuss your experience with them. This shows genuine interest and preparation.
✨Ask Insightful Questions
Prepare thoughtful questions about the team’s current projects, challenges they face, or their vision for MLOps. This not only shows your enthusiasm for the role but also helps you gauge if the company is the right fit for you.
