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Salary
≈ $62k – $160k per year (Estimated)
Location
In office (Helsinki, Stockholm)
Seniority
Senior · 5+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 15, 2026. First seen by Alion on May 6, 2026. Qutwo scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Qutwo is a private quantum AI lab in Europe that builds AI to help industry leaders gain a competitive advantage. It partners with large enterprises in Finland, the Nordics and internationally, and hires quantum algorithm researchers, AI and optimization scientists, MLOps engineers and platform architects. The company is headquartered in Helsinki, Finland.
Backed by D11Z. Ventures

JoinQutwo - Europe's private Quantum AI Lab, on our quest to bridge the gap between the classical and the quantum world. We partner with the most advanced and forward-thinking customers, solving fundamental real-world problems, side by side.

We are seeking an exceptional DevOps and MLOps Engineer to build and maintain CI/CD pipelines, cloud infrastructure, and ML operations workflows that enable Qutwo to ship reliably and continuously. You will work across engineering and research teams, supporting both platform development and client-facing AI projects.

Requirements

  • 5+ years of actual production experience in DevOps, Platform Engineering, or MLOps. You’ve owned infrastructure at scale and have the scar tissue to prove it.

  • Deep Kubernetes & Docker knowledge. You know how to debug K8s networking, handle node evictions, and optimize containers for production, not just local dev.

  • Production-grade IaC & CI/CD. You write clean, modular Terraform (or similar) and design reliable, multi-environment pipelines that don't constantly break.

  • Strong Python & Bash scripting. You write clean, maintainable code to automate complex tasks and build internal tooling.

  • Real observability experience. You’ve used Prometheus, Grafana, and OpenTelemetry to actually diagnose and solve production outages, not just stare at dashboards.

  • ML Infrastructure. You either have experience with ML pipelines and model deployment, or you're a senior engineer who is genuinely excited to dive deep into MLOps.

  • Comfortable with ambiguity. We move fast, and our infrastructure needs to evolve with the business. You’re someone who figures things out and helps the team grow.

Experience in one or more of the following areas is a plus but not a requirement:

  • Quantum computing or scientific computing environments.

  • High-performance computing environments.

  • Enterprise SaaS platform development.

  • GPU workload orchestration.

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