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5 дней назад

Software Engineer Intern (AI)

7 000 - 8 000$
Формат работы
onsite
Тип работы
fulltime
Грейд
trainee
Английский
b2
Страна
US
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

Текст:
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TL;DR
Software Engineer Intern (AI): Designing, developing, and deploying inference solutions for AI models at scale with an accent on Python, C++, CUDA, NCCL, and high-performance model serving. Focus on optimizing inference systems, monitoring live services, debugging production code, and shipping features for LLM and multimodal model infrastructure.

Location: In office in Palo Alto, California, USA

Salary: USD 7,000–8,000 per month

Company

hirify.global builds AI model-serving infrastructure for large language models and multimodal models.

What you will do

  • Design, develop, and test inference solutions for AI models.
  • Implement and optimize models using Python, C++, CUDA, and NCCL.
  • Monitor and maintain live services.
  • Develop features, fix bugs, review code, and improve software quality.
  • Participate in stand-ups, design discussions, and collaboration with engineering and cross-functional teams.
  • Explore industry developments in AI and machine learning and ship practical improvements.

Requirements

  • Currently pursuing a Bachelor's or Master's degree in Computer Science, Computer Engineering, or a related field.
  • Strong knowledge of data structures, algorithms, and software design patterns.
  • Proficiency in Python and experience with AI/ML libraries or frameworks such as NumPy, pandas, SciPy, TensorFlow, or PyTorch.
  • Familiarity with AI models, Transformers, and Diffusers.
  • Experience with Git and agile development methodologies.
  • Strong debugging, optimization, communication, and teamwork skills.

Culture & Benefits

  • Work on AI model-serving systems powering LLM and multimodal applications.
  • Join a small team where work ships directly to customers.
  • Learn from engineers building high-performance inference systems at scale.
  • Work in a fast-paced environment with ownership, autonomy, and end-to-end responsibility.
  • Initiative, drive, and persistence are valued when solving complex infrastructure problems.

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