Qutwo
Qutwo
Qutwo ir mākslīgā intelekta laboratorija un programmatūras uzņēmums, kas darbojas mākslīgā intelekta, kvantu datošanas un uzņēmumu optimizācijas krustpunktā. Tā platforma Qutwo OS palīdz komandām izstrādāt kvantu un hibrīdā mākslīgā intelekta algoritmus, savienot augstas veiktspējas datošanu, grafiskos procesorus un dažādu veidu kvantu procesorus, kā arī darbināt ražošanas slodzes, izmantojot datu apstrādes konveijerus, uzraudzību un noturību pret kļūmēm. Qutwo atbalsta klientus arī ar pētniecības partnerībām, pie klientiem strādājošiem zinātniekiem un integrācijas pakalpojumiem, kuru mērķis ir pārvērst progresīva mākslīgā intelekta un kvantu datošanas eksperimentus praktiskās uzņēmumu lietotnēs. Starptautiskajā komandā ir mākslīgā intelekta un kvantu zinātnes pētnieki un inženieri, un uzņēmums meklē darbiniekus mākslīgā intelekta, MLOps un DevOps, kvantu algoritmu un platformu inženierijas jomās.

Senior Site Reliability Engineer in Helsinki (Hybrid)

Lead reliable, secure multi-cloud Kubernetes infrastructure for Qutwo’s quantum-AI platform. Operate distributed machine-learning workloads while advancing observability, GitOps, and CI/CD.

Apraksts

  • Design and run Kubernetes infrastructure across multiple cloud platforms
  • Develop metrics, logging, tracing, and alerting capabilities
  • Establish practical service-level objectives and incident-response processes
  • Automate reproducible, reviewable environments with infrastructure as code and GitOps
  • Manage scheduling, autoscaling, and cost efficiency for distributed training and inference, including Ray clusters on Kubernetes
  • Protect platforms through secrets management, network policies, workload identity, and supply-chain security
  • Create CI/CD and deployment platforms for engineers and coding agents
  • Maintain documentation for infrastructure and architectural decisions

Prasības

  • Seven or more years of experience building and operating production systems, including substantial work in SRE, platform, or infrastructure engineering
  • Advanced practical knowledge of Kubernetes, including cluster operations, networking, storage, and troubleshooting
  • Experience operating platforms across multiple cloud providers and evaluating their trade-offs
  • Strong infrastructure-as-code and automation capabilities with tools such as Terraform, Helm, and GitOps
  • Proficiency in Python or Go for developing engineering tools
  • Sound understanding of distributed systems, failure scenarios, and reliability trade-offs
  • Security-focused approach to trust boundaries, identity, secrets, and software supply chains
  • Ability to use AI-assisted development tools and critically review coding-agent output, including infrastructure changes
  • Fluent English communication skills
  • Demonstrated effectiveness in agile, cross-functional teams

Priekšrocības

  • Hybrid working arrangement in Helsinki
  • Chance to establish reliability practices and infrastructure foundations
  • Exposure to distributed machine-learning workloads, quantum-AI systems, and multi-cloud environments
  • Collaborative, agile, cross-functional working culture

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