Nebius предлагает чётко очерченную практическую роль для старта в сфере AI-облачной инфраструктуры, с понятными целями обучения и возможностью продолжить работу на полной ставке; однако из-за срока всего в три месяца и неуказанной оплаты долгосрочные перспективы и уровень дохода остаются неопределёнными.
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Всего три месяцаОплата не раскрытаПонятные задачиСфера AI-инфраструктурыОпыт и развитие
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Текст:
Hirify AI/Оригинал
TL;DR
Technical Operations & Project Management (Early Talent) (AI cloud infrastructure): Monitoring and improving GPU node repair, node acceptance, and infrastructure maintenance processes across data centers with an accent on operational metrics, SLA compliance, and cross-functional coordination. Focus on investigating repair and acceptance bottlenecks, coordinating maintenance activities, and improving dashboards, documentation, and ticketing processes.
Location: Amsterdam or Tel-Aviv. The program lasts 3 months and starts in January 2027. Applicants must be authorized to work in the country where they apply.
Compensation: Paid; competitive compensation.
Company
Nebius builds a full-stack AI cloud platform supporting data preparation, model training, and production deployment, with infrastructure spanning compute, storage, networking, and applied AI.
What you will do
Monitor GPU node availability, repair backlogs, acceptance results, operational metrics, and SLA compliance across regions and clusters.
Track failed acceptance tests, delayed repairs, outstanding actions, and dependencies, following up with responsible engineering teams.
Investigate recurring repair and acceptance issues with Hardware Infrastructure and Platform teams and identify process improvements.
Maintain operational dashboards, Jira tickets, status reports, monitoring procedures, and documentation.
Help plan and coordinate smaller infrastructure maintenance activities, including network switch replacements, timelines, checklists, communications, and execution reporting.
Support additional initiatives such as extending node repair processes to CPU and worker nodes and improving Major Maintenance documentation.
Requirements
Currently completing or recently completed a degree in engineering, computer science, information systems, operations management, or a related field.
Strong analytical and problem-solving skills, with the ability to work with data and operational metrics.
Ability to organize information, track multiple activities, and follow up on outstanding tasks.
Clear communication skills and comfort collaborating with technical specialists and managers.
Proactive approach to identifying problems and investigating their causes rather than only reporting them.
Ability to work with established processes while identifying opportunities to improve them.
Attention to detail and responsibility for completing assigned tasks.
Interest in cloud infrastructure, technical operations, and cross-functional project management.
Work authorization in the country where the applicant applies.
Nice to have
Basic knowledge of cloud infrastructure, servers, networking, or data center operations.
Experience with monitoring or data visualization tools such as Grafana.
Familiarity with SQL or other data analysis tools.
Experience with Jira, Confluence, or similar collaboration tools.
Experience coordinating university, volunteer, or personal projects involving multiple participants.
Interest in infrastructure operations, reliability engineering, or technical project management.
Culture & Benefits
Hands-on experience operating and maintaining large-scale AI cloud infrastructure.
Exposure to infrastructure failure detection, investigation, resolution, operational monitoring, SLA management, and incident prevention.
Collaboration with hardware infrastructure, compute, networking, and platform engineering teams.
Career growth and learning opportunities, with flexibility and ownership.
Collaborative, innovative, and international working environment with work on impactful AI projects.
Potential discussion of a full-time continuation opportunity after the program, subject to performance, mutual fit, and business needs.
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