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InternУдалённоКонтракт

AI/ML Specialist Solution Architect (Early Talent)

Оценка ИИ

Отличная возможность для старта карьеры в топовой технологической компании, работающей с передовым оборудованием (NVIDIA Blackwell). Программа предлагает менторство, конкурентную оплату и реальную перспективу перехода в штат.


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Сложность вакансии

ЛегкоСложно
Оценка ИИ

Позиция ориентирована на начинающих специалистов (стажеров или выпускников), поэтому требования к опыту минимальны. Основная сложность заключается в необходимости иметь хорошую теоретическую базу в ML и облачной инфраструктуре, а также пройти отбор в быстрорастущую международную компанию.

Анализ зарплаты

Медиана7 500 $
Рынок5 000 $ – 10 000 $
Оценка ИИ

Для позиции стажера или начинающего специалиста в области AI/ML в США рыночные ставки варьируются от $30 до $60 в час (или $5,000–$10,000 в месяц). Nebius заявляет о конкурентной оплате, что обычно соответствует верхнему сегменту для талантливых выпускников в сфере Cloud/AI.

Сопроводительное письмо

I am writing to express my strong interest in the AI/ML Specialist Solution Architect (Early Talent) position at Nebius. As a student/recent graduate with a deep passion for AI infrastructure and cloud computing, I have closely followed Nebius's rapid growth and its commitment to providing cutting-edge GPU cloud solutions. My background in Computer Science, combined with hands-on experience in Python and PyTorch, aligns perfectly with the technical requirements of this role.

During my academic projects, I have explored distributed systems and machine learning workflows, which has sparked my interest in how large-scale AI systems are architected. I am particularly excited about the opportunity to learn from your experienced team and contribute to designing solutions on NVIDIA Hopper and Blackwell platforms. I am a proactive learner with strong communication skills, ready to help Nebius customers successfully adopt and scale their AI workloads.

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Откликнитесь в nebius уже сейчас

Присоединяйтесь к Nebius и начните свою карьеру в авангарде облачных вычислений для ИИ уже сегодня!

Описание вакансии

Why work at NebiusNebius is leading a new era in cloud computing to serve the global AI economy. We create the tools and resources our customers need to solve real-world challenges and transform industries, without massive infrastructure costs or the need to build large in-house AI/ML teams. Our employees work at the cutting edge of AI cloud infrastructure alongside some of the most experienced and innovative leaders and engineers in the field.

Where we workHeadquartered in Amsterdam and listed on Nasdaq, Nebius has a global footprint with R&D hubs across Europe, North America, and Israel. The team of over 1400 employees includes more than 400 highly skilled engineers with deep expertise across hardware and software engineering, as well as an in-house AI R&D team.

Summary:

Location: Remote from USA

Duration: 3 months

Start date: June 2026 

Compensation: Paid

Eligibility: Current University student (Computer Science or related field), Recent Graduate or Early Career specialist

Why work at NebiusNebius is leading a new era in cloud computing to serve the global AI economy. We create the tools and resources our customers need to solve real-world challenges and transform industries, without massive infrastructure costs or the need to build large in-house AI/ML teams. Our employees work at the cutting edge of AI cloud infrastructure alongside some of the most experienced and innovative leaders and engineers in the field.

Listed on Nasdaq, Nebius has a global footprint with R&D hubs across Europe, North America, and Israel. The team of over 1400+ employees includes more than 400 highly skilled engineers with deep expertise across hardware and software engineering, as well as an in-house AI R&D team.

The role

Customer experience at Nebius AI Cloud focuses on helping customers successfully adopt and scale AI workloads. As an intern, you’ll support this mission by learning how real-world AI systems are designed, deployed, and optimized at GPU cloud scale. You’ll gain exposure to modern ML frameworks, large-scale GPU infrastructure (including NVIDIA Hopper, Blackwell and Grace Blackwell platforms), and the collaboration between customers, engineering, and product teams.

This role offers a strong learning environment with mentorship, minimal bureaucracy, and opportunities to develop both technical and communication skills.

We are looking for an AI/ML Solutions Architect Intern to support AI-focused customers using Nebius services. This is a learning-focused role designed for students or early-career candidates who are interested in AI infrastructure, cloud platforms, and applied machine learning.

You will work closely with experienced Solutions Architects, Engineers, and Product teams to help design, document, and support AI solutions.

Your responsibilities will include:

  • Assist in designing and documenting AI and ML solutions.
  • Learn how distributed training and inference workloads run on multi-GPU cloud-based systems.
  • Help prepare technical materials such as presentations, documentation, tutorials, or demos.
  • Participate in investigation, troubleshooting and optimization tasks under guidance from senior team members.

We expect you to have:

  • Currently pursuing or recently completed a degree in Computer Science, Engineering, Data Science, or a related field.
  • Solid understanding of machine learning concepts and workflows.
  • Familiarity with at least one ML framework such as PyTorch, TensorFlow, or JAX.
  • Comfort with programming in Python (other languages are a plus).
  • Interest in cloud infrastructure, GPUs, and large-scale AI systems.
  • Strong communication skills and a willingness to learn and ask questions.

Nice to have:

  • Exposure to Kubernetes, Docker, or other container technologies.
  • Familiarity with Git or basic DevOps workflows.
  • Coursework or projects involving distributed systems, MLOps, or deep learning.
  • Experience with AI projects from school, hackathons, or personal work.

Tools you may learn and use:

  • Programming: Python (plus exposure to Go, Java, or C++).
  • ML Frameworks: PyTorch, TensorFlow, JAX, Hugging Face.
  • Infrastructure & DevOps: Docker, Git, Kubernetes, Terraform.
  • Schedulers & Orchestration: Kubernetes, Slurm (learning-focused).

What we offer

  • Competitive salary and comprehensive benefits package.
  • Mentorship from experienced AI, ML, and cloud infrastructure professionals.
  • Hands-on experience with real customer workloads and production systems.
  • Remote work flexibility and a collaborative, supportive team environment.
  • Opportunity to be considered for a full-time role after the Program.

We’re growing and expanding our products every day. If you’re up to the challenge and are excited about AI and ML as much as we are, join us!

What we offer

  • Competitive salary and comprehensive benefits package.
  • Opportunities for professional growth within Nebius.
  • Flexible working arrangements.
  • A dynamic and collaborative work environment that values initiative and innovation.

We’re growing and expanding our products every day. If you’re up to the challenge and are excited about AI and ML as much as we are, join us!

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Навыки

  • Python
  • PyTorch
  • TensorFlow
  • JAX
  • Docker
  • Kubernetes
  • Git
  • Terraform
  • Machine Learning
  • Cloud Infrastructure
  • Distributed Systems

Возможные вопросы на собеседовании

Проверка базовых знаний архитектуры нейросетей и понимания процесса обучения.

Можете ли вы объяснить разницу между обучением модели на одном GPU и распределенным обучением на нескольких узлах?

Оценка навыков владения основным инструментом разработки.

Опишите ваш опыт работы с PyTorch или TensorFlow: какие проекты вы реализовывали и с какими трудностями сталкивались?

Проверка понимания специфики работы Solution Architect.

Как бы вы объяснили клиенту преимущества использования GPU-облака Nebius для инференса больших языковых моделей (LLM)?

Оценка интереса к инфраструктурной части ИИ.

Что вы знаете о контейнеризации (Docker/Kubernetes) и почему она важна для развертывания ML-моделей?

Проверка soft skills и умения работать в команде.

Расскажите о ситуации, когда вам нужно было быстро освоить новую технологию для решения задачи. Как вы подходили к процессу обучения?

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