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DeepL

Staff Platform Engineer

London
Posted about 15 hours ago
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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 a self-service foundation they can build on.

Your responsibilities

  • Take ownership of the reliability, capacity and cost efficiency of DeepL's compute infrastructure, CPU and GPU: the hybrid platform serving our products across AWS and on-prem, and the on-prem clusters powering our research, including their hardware lifecycle
  • Shape the platform's architecture: bring strong technical positions, weigh them on their merits with your peers, and commit to decisions serving the best outcome
  • Design, build and operate production-grade Kubernetes clusters across cloud and on-prem infrastructure, taking them from design through to long-term operation
  • Drive the technical work of deepening the hybrid model - unifying how workloads run across on-prem hardware and cloud, especially AWS and supporting research as it adopts cloud-native technology and ways of working
  • Define infrastructure-as-code and platform standards that hold across the track, and strengthen observability and security so the platform's behaviour is legible to the teams that depend on it
  • Mentor engineers across the infrastructure track and raise the technical bar of the group, through design reviews, architecture decisions and the everyday habits that keep the platform maintainable
  • Build consensus across engineering teams and turn it into shipped change, shaping platform direction at track level
  • Lead incident response for hybrid infrastructure, driving remediation through to root cause, and help sustain an on-call rotation the team can carry for the long term

Reasons to use Rodeo

I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?

Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.

Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.

Start with a chat, not a search bar

Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.

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Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.

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It searches the market for you

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Why you're a good match

You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.

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Strong

Experience fit

Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.

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Only hits

No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.

What you bring to the table

  • Deep, hands-on Kubernetes expertise: you have designed, built and operated clusters at scale, through their full lifecycle
  • Depth at scale in either public cloud or on-prem infrastructure, plus the credibility to work in the other. AWS experience is preferred, and bare-metal or data centre experience is strongly valued
  • Networking and Linux depth you can debug with: you can follow a problem from a container through the host to the network edge
  • Infrastructure as code with Terraform or equivalent, and GitOps delivery with tooling such as ArgoCD, applied to environments you have owned in production
  • Software engineering skills in at least one major language, Go or Python preferred, at the level of building tooling other engineers rely on
  • A track record of technical ownership spanning several teams: you create clarity where a mandate crosses team boundaries, hold clear technical positions, change them on evidence and carry other engineers with you
  • Strong incident-management and reliability-engineering discipline, and the ownership mindset to build more resilient systems

You’d get bonus points for

  • GPU infrastructure for training or inference at scale
  • Distributed storage systems in production, such as Ceph
  • Having served researchers or data scientists as platform customers
  • Networking at BGP level in a hybrid or on-prem environment

What we offer:

  • Diverse and internationally distributed team: joining our team means becoming part of a large, global community with people of more than 90 nationalities. We're more than just colleagues; we're a group of professionals with a shared mission to connect diverse cultures. Our global presence is growing–we've doubled in size nearly every year, with our employees based in the UK, Germany, the Netherlands, Poland, the US, and Japan, and we continue to expand our network.
  • Open communication, regular feedback: as a language-focused company, we value the importance of clear, honest communication. We value smooth collaboration, direct and actionable feedback, and believe that leading with empathy and growth mindset makes us better together.
  • Hybrid work, flexible hours: we offer a hybrid work schedule, with team members coming into the office twice a week. This allows you to engage directly with your team and experience the unique energy of our workspace, while still enjoying the flexibility and comfort of working from home. With flexible working hours and trust in your productivity, we are in sync with your team's general locations and time zones to foster effective and seamless collaboration.
  • Virtual Shares - An ownership mindset in every role. We believe everyone should share in our success, and that’s why every employee receives Virtual Shares, linking your contribution directly to DeepL’s growth and rewarding you with a stake in our future.
  • Regular in-person team events: we bond over vibrant events that are as unique as our team, from local team and business unit gatherings, to new-joiner onboardings, to company-wide events that bring us all together–literally.
  • Monthly full-day hacking sessions: every month, we have Hack Fridays, where you can spend your time diving into a project you're passionate about and get the opportunity to work with other teams–we value your initiatives, impact, and creativity.
  • 30 days of annual leave: we value your peace of mind. With 30 days off (excluding public holidays) and access to mental health resources, we make sure you're as strong mentally as you are professionally.
  • Competitive benefits: just as our team spans the globe, so does our benefits package. We've crafted it to reflect the diversity of our team and tailored it to align with your unique location, to ensure you feel supported every step of the way.

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If this role and our mission resonate with you, but you're hesitant because you don't check all the boxes, don't let that hold you back. At DeepL, it's all about the value you bring and the growth we can foster together. Go ahead, apply, let's discover your potential together. We can't wait to meet you!

We are an equal opportunity employer

You are welcome at DeepL for who you are - we appreciate authenticity here. Our product is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all succeed, contribute, and think forward! So bring us your personal experience, your perspectives, and your background. It’s in our diversity that we will find the power to break down language barriers in the world.

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Skills

Kubernetes
AWS
Linux
Terraform
GitOps
ArgoCD
Go
Python
Infrastructure as code
Networking
GPU infrastructure
Distributed storage
Ceph
Incident management
Reliability engineering

Location

London, England, United Kingdom

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