GenAI Engineer Intern — Shape the Next-Gen Structural Copilot

Genia

Singapore

On-site

SGD 33,480 - 55,800

Full time

14 days+

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Benefits offered by this job

Hands-on experience with AI R&D
Mentorship from senior AI engineers
Potential full-time offer for outstanding performers

Job summary

A forward-thinking AI startup in Singapore is looking for a Generative AI Engineer Intern. You will assist in R&D efforts for next-generation AI technologies, including fine-tuning Large Language Models and experimenting with Graph Neural Networks. This internship offers hands-on experience with cutting-edge AI applications tailored for the architecture and engineering sectors. Ideal candidates are pursuing relevant degrees and possess foundational knowledge in machine learning and AI frameworks, demonstrating curiosity and self-motivation.

Qualifications

  • Currently pursuing relevant degree in AI, Machine Learning, or a related field.
  • Familiarity with frameworks like PyTorch, TensorFlow, or JAX.
  • Curiosity about applications of AI in architecture, engineering, and construction.

Responsibilities

  • Assist in fine-tuning and evaluating Large Language Models for architecture and engineering.
  • Support experiments with Graph Neural Networks on structured engineering data.
  • Document processes and write benchmark results.

Skills

Familiarity with Large Language Models
Exposure to Graph Neural Networks
Basic understanding of image generation models
Proficiency in Python
Experience in AI/ML-related research

Education

Currently pursuing a Bachelor's, Master's, or PhD degree in Computer Science or related field

Tools

HuggingFace Transformers
PyTorch
TensorFlow
JAX

Job description

A forward-thinking AI startup in Singapore is looking for a Generative AI Engineer Intern. You will assist in R&D efforts for next-generation AI technologies, including fine-tuning Large Language Models and experimenting with Graph Neural Networks. This internship offers hands-on experience with cutting-edge AI applications tailored for the architecture and engineering sectors. Ideal candidates are pursuing relevant degrees and possess foundational knowledge in machine learning and AI frameworks, demonstrating curiosity and self-motivation.
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