Datacentre Ops Engineer: GPU/HPC & Liquid Cooling (Hybrid) in London
Thor London About the role
Thor in the London area is seeking a hands-on Datacentre Operations Engineer to manage high‑density GPU systems, liquid cooling, and complex cabling.
You’ll own break/fix execution, DLC/CDU maintenance, capacity tracking and 24x7 incident response for a fast-growing AI/HPC infrastructure.
The role requires 3+ years in data centre operations or related hardware roles, plus hands-on experience with NVIDIA GPU platforms, high‑performance storage and networking.
UK right to work is required.
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Your tasks
Manage high-density GPU systems and liquid cooling in a fast-paced environment.
Your profile
3+ years in data centre operations and hands-on experience with NVIDIA GPUs.
What's also included
Hybrid work model, competitive salary, and opportunities for professional growth.
Tech stack & ways of working
Datacentre Ops Engineer: GPU/HPC & Liquid Cooling (Hybrid) in London employer: Thor
Thor is an exceptional employer that fosters a dynamic and ambitious work culture, perfect for those looking to excel in their careers. With a clear pathway to Director level and opportunities for extensive international travel, employees are encouraged to grow professionally while enjoying competitive compensation and unique perks. Join us in London and be part of a high-performing team that values performance and rewards success.
Your perspectives
Be at the forefront of cutting-edge technology and make a real impact.
StudySmarter Expert Advice
Get Involved in Data Science Meetups
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Thor.
Apply Directly through Our Website
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Some tips for your application 🫡
Show Off Your Projects
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How to prepare for a job interview at Thor
Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
Get Comfortable with Python and R
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Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
Locations
- London
