AI Research Intern

1 week ago

Singapore DECIATO PTE. LTD. Full time $60,000 - $120,000 per year

We are seeking a deeply curious AI Research Intern to join our team in building and training the next generation of Causal AI models. You will work alongside our senior researchers to design, implement, and test models that learn the "physics" of complex systems.

This role is focused on pure research and development. You will be helping to run large-scale simulations, analyze the results of "hero training runs," and implement novel architectures to push the boundaries of AI in our target industries.

What You Will Do
  • Model Implementation: Implement and test novel AI and ML model architectures (e.g., in PyTorch, JAX, or TensorFlow) based on specifications from the research team.
  • Run Large-Scale Simulations: Use our internal AI platform to run large-scale experiments, including "self-play" and reinforcement learning loops, on complex, multimodal datasets.
  • Data Analysis & Visualization: Analyze and visualize the outputs of model training runs and simulations to help uncover new insights, identify failure modes, and suggest improvements.
  • Dataset Preparation: Assist in preprocessing, cleaning, and versioning the massive datasets required for our "world models."
  • Benchmark & Validate: Help benchmark our models against existing SOTA (State-Of-The-Art) and validate their performance on simulated and real-world data.
  • Literature Review: Stay on top of cutting-edge research in Causal AI, Reinforcement Learning, and complex systems, presenting key findings to the team.
Ideal Candidate Profile
  • Academic Background: Currently pursuing an M.S. or Ph.D. (or an advanced B.S. with research experience) in Computer Science, AI, Machine Learning, Physics, or a related quantitative field.
  • Strong Coder: Deep proficiency in Python and extensive hands-on experience with modern ML frameworks like PyTorch, JAX, or TensorFlow.
  • Deep ML/AI Interest: A strong foundation in machine learning, deep learning, and ideally, reinforcement learning (RL) or causal inference.
  • First-Principles Thinker: You are driven by curiosity and a desire to understand complex systems from the ground up. You are comfortable with ambiguity and "unsolvable" problems.
  • Data-Driven & Rigorous: You have a strong quantitative and analytical background, with a methodical approach to experimentation.
  • Mission-Aligned: You are excited by the prospect of modeling complex "physics" in finance, aviation, or energy, not just optimizing ad clicks.

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