AI Summer Internship: Hands-on ML & CV in Islamabad

Pakistan IT Jobs

Islamabad

Vor Ort

PKR 167.000 - 246.000

Vollzeit

14 Tage+

Eine vollständige Bewerbung in einer Minute

Maßgeschneiderter Lebenslauf und Anschreiben – versandbereit.

Schaffe es an den ATS-Filtern vorbei

Benefits dieser Stelle

Internship completion certificate
Mentorship from AI engineers
Possible full-time opportunity

Zusammenfassung

Rapids AI invites students and recent graduates to join the AI Summer Internship Program 2026 in Islamabad. You’ll work on production-grade AI projects, gaining hands-on experience in AI/ML, CV, and LLMs under mentorship from seasoned engineers.

The program offers on-site work at ISLAMABAD with a 2-3 month duration, flexible hours, and potential for full-time opportunities based on performance. Paid or unpaid based on skills and interview outcomes.

Qualifikationen

  • Currently enrolled BS/MS student or new graduate in Computer Science, AI, Data Science, Software Engineering or related fields.
  • Basic proficiency in Python and understanding of AI/ML fundamentals.
  • Strong problem-solving skills and willingness to learn.

Aufgaben

  • Contribute to real-world AI projects under guidance of experienced engineers.
  • Collaborate with AI engineers to implement experiments and pipelines.
  • Learn modern AI technologies and workflows through hands-on tasks.

Kenntnisse

Python basics
AI/ML fundamentals
Problem-solving
Willingness to learn

Ausbildung

BS/MS in CS/AI/Data Science/Software Engineering

Tools

PyTorch
TensorFlow
OpenCV
Hugging Face
LangChain
LangGraph
RAG
Fine-Tuning

Jobbeschreibung

Rapids AI invites students and recent graduates to join the AI Summer Internship Program 2026 in Islamabad. You’ll work on production-grade AI projects, gaining hands-on experience in AI/ML, CV, and LLMs under mentorship from seasoned engineers.

The program offers on-site work at ISLAMABAD with a 2-3 month duration, flexible hours, and potential for full-time opportunities based on performance. Paid or unpaid based on skills and interview outcomes.

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