Staff Platform Engineer

DeepL

London · Onsite · Full Time

Posted

Job description

Meet DeepL DeepL is a global AI product and research company focused on building secure, intelligent solutions to complex business problems. Over 200,000 business customers and millions of individuals across 228 global markets today trust DeepL's Language AI platform for human-like translation, improved writing and real-time voice translation. Founded in 2017 by CEO Jaroslaw “Jarek” Kutylowski, DeepL now has around 1,000 passionate employees and is supported by world-renowned investors including Benchmark, IVP, and Index Ventures. Our goal is to become the global leader in trusted, intelligent AI technology, building products that drive better communication, foster connections, and create a meaningful impact. To achieve this, we need talented people like you to join our journey. If you’re ready to shape the future of AI and grow your career in a fast-moving, purpose-driven environment, DeepL is your next destination. What sets us apart What sets us apart is our blend of cutting-edge AI technology, meaningful work, and a culture where people truly thrive. We’re a team of innovators, researchers, and creators driven by a shared purpose to unlock human potential by making work simpler, smarter, and more connected. When we share what it’s like to work at DeepL, the reactions are overwhelmingly positive. This might be because of our technology that helps millions of people and businesses communicate and work better every day, or because of the trust, curiosity, and care that shape our culture. What we know for sure is this: being part of DeepL means joining a team dedicated to innovation, growth, and well-being. Discover more about life at DeepL on LinkedIn , Instagram , and our Blog . Meet the team behind this journey You will join the Hybrid Platform Engineering track, which builds and operates the compute layer underpinning DeepL's products and research: the Kubernetes control plane, node lifecycle, networking, storage and core cluster services, across both on-prem and cloud infrastructure. Today that spans hybrid infrastructure in Europe - including large on-prem GPU clusters powering DeepL's research and hundreds of on-prem GPU nodes serving production inference - as well as AWS regions across the globe running the product. The track is deepening this hybrid model, unifying how workloads run across on-prem hardware and AWS to give product and research teams…

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