At a Glance
- Tasks: Build and maintain high-performance data pipelines for large datasets.
- Company: Pioneering AI company in Greater London with a people-first culture.
- Benefits: Fully remote work, flexible hours, vacation days, and continuous learning opportunities.
- Other info: Join a dynamic team focused on innovation and growth.
- Why this job: Contribute to the development of cutting-edge foundation models in a collaborative environment.
- Qualifications: Experience in data engineering and a passion for machine learning.
The predicted salary is between 50000 - 70000 £ per year.
A pioneering AI company in Greater London seeks a talented data engineer to join their Pretraining Data team. In this hands-on role, you will build and maintain high-performance pipelines for processing large datasets, contributing directly to the development of foundation models.
The position offers a fully remote work environment with flexible hours, vacation days, and a people-first culture, emphasizing collaboration and continuous learning.
Data Engineer – Large-Scale ML Data Pipelines (Remote) employer: poolside
Join a pioneering AI company in Greater London that prioritises a people-first culture, offering flexible remote work and a commitment to employee growth through continuous learning. As a Data Engineer, you'll be part of an innovative team dedicated to building high-performance data pipelines, with ample opportunities for collaboration and professional development.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer – Large-Scale ML Data Pipelines (Remote)
✨Tip Number 1
Network like a pro! Reach out to folks in the AI and data engineering space on LinkedIn. Join relevant groups and participate in discussions to get your name out there.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving large-scale ML data pipelines. This will give potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge. Be ready to discuss your experience with data processing and any challenges you've overcome in past projects.
✨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, we love seeing candidates who are proactive!
We think you need these skills to ace Data Engineer – Large-Scale ML Data Pipelines (Remote)
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights relevant experience in building and maintaining data pipelines. We want to see how your skills align with the role, so don’t be shy about showcasing your achievements!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re excited about the role and how you can contribute to our Pretraining Data team. Keep it engaging and personal – we love to see your personality!
Showcase Your Technical Skills:Don’t forget to mention the specific tools and technologies you’ve worked with. Whether it’s Python, SQL, or any other tech, we want to know how you’ve used them to tackle challenges in data engineering.
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 – just a few clicks and you’re done!
How to prepare for a job interview at poolside
✨Know Your Data Pipelines
Make sure you brush up on your knowledge of data pipelines, especially in the context of large-scale machine learning. Be ready to discuss your experience with building and maintaining these systems, as well as any specific tools or technologies you've used.
✨Showcase Your Problem-Solving Skills
Prepare to share examples of challenges you've faced in previous roles and how you overcame them. This role is hands-on, so demonstrating your ability to troubleshoot and optimise data processes will impress the interviewers.
✨Emphasise Collaboration
Since the company values a people-first culture, be sure to highlight your teamwork experiences. Discuss how you've collaborated with others in past projects, particularly in data engineering or related fields, to show that you're a good fit for their collaborative environment.
✨Ask Insightful Questions
Prepare thoughtful questions about the company's approach to data engineering and their future projects. This shows your genuine interest in the role and helps you gauge if the company aligns with your career goals, especially in a remote setting.
