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The Swiss National Supercomputing Centre (CSCS) develops and operates a high-performance computing and data research infrastructure that supports world-class science in Switzerland. Its user laboratory is available to domestic and international researchers in academia, industry, and the business sector. The centre is operated by ETH Zurich and has offices at its data centre in Lugano and in Zurich. For this position, the preferred work location is Lugano, but Zürich is also acceptable. Project background We are seeking a versatile and driven DevOps Engineer to help design, build, and operate the software-defined infrastructure and services powering advanced scientific computing and AI/ML workloads at scale. You will work at the intersection of systems engineering, software engineering, cloud-native infrastructure, and high-performance computing (HPC), contributing to platforms and services used by researchers and engineers tackling complex scientific and AI challenges. We value strong engineering fundamentals, curiosity, adaptability, and willingness to learn more than a perfect initial match of technical requirements. We welcome engineers from diverse backgrounds who are eager to contribute and grow. If you are motivated by challenging technical environments and enjoy understanding systems deeply, we strongly encourage you to apply even if your experience does not cover every area listed below. We are offering a contract initially limited to two years , which will provide the opportunity to contribute to a fast-evolving AI landscape in which CSCS plays a key role and to support high-impact initiatives both nationally and internationally. This includes contributions to the Swiss AI Initiative and similar programs, such as lending support for the development and release of the Apertus models. The initial two-year contract could potentially be extended or even become permanent. Job description Design, deploy, automate, and operate scalable infrastructure and cloud-native platform services Contribute to Kubernetes-based AI/ML and HPC platforms, including CI/CD, GitOps, observability, security, and operational tooling Collaborate with researchers and engineers to support complex workflows, troubleshoot production environments, and improve reliability and performance Contribute to platform engineering, automation, and developer productivity initiatives across evolving systems and services The technologies and areas below illustrate the breadth of our environment and interests. They are not a checklist of requirements, and experience in only some of these areas is expected Profile The technologies and areas below illustrate the breadth of our environment and interests. They are not a checklist of requirements, and experience in only some of these areas is expected. Technical environment and areas of interest: Linux systems engineering, scripting, troubleshooting, and software development (e.g., Python, Bash) Containers, Kubernetes, CI/CD, GitOps, and Infrastructure as Code (e.g., Terraform, Helm, Ansible, ArgoCD) Distributed systems concepts, APIs, scalability, observability, identity and access management, and security AI/ML platforms and supporting infrastructure services HPC systems, GPU clusters, and large-scale infrastructure environments Platform engineering and developer productivity tooling Secure or confidentiality-sensitive operational environments Personal qualities: Curious, hands-on, and eager to understand systems inside-out Strong engineering mindset and problem-solving attitude Comfortable learning new technologies and working across disciplines Effective communicator and collaborative team player Ways to stand out from the crowd: Experience supporting research or scientific computing environments Familiarity with HPC systems and services Exposure to GPU clusters and accelerated computing Experience with SRE practices or on-call operations Advanced Linux security knowledge Ability to leverage AI-assisted software development for increased productivity Our core values as guiding principles: Curiosity: You enjoy learning and understanding systems deeply Openness: You collaborate effectively and value different perspectives Courage: You are willing to tackle difficult or unfamiliar problems Supportive: You help colleagues and users succeed Integrity: You act responsibly, reliably, and transparently Curious? So are we. Read more about the position here: https://jobs.ethz.ch/job/view/JOPG_ethz_pPQbOEVFpuNEe6dwGQ
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.