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ModalModalNew York, NY

Research Intern

PhD research intern role focused on advancing reinforcement learning, machine learning, and foundation models. Work on large-scale training, optimization, inference, long-context tasks, and improving efficiency, reliability, and robustness for real-world AI deployments.

168k – 168k/yr
On-siteAI Research

About the role

Responsibilities

  • Improve existing methods and develop new techniques for large-scale model training, optimization, and inference.
  • Extend models to long-context and long-horizon tasks.
  • Improve inference-time efficiency, reliability, and robustness in high-stakes real-world deployments.

Requirements

  • Currently pursuing a PhD in computer science, machine learning, or a related field.
  • Demonstrated record of research in reinforcement learning, machine learning, foundation models, or related areas.
  • Experience developing and evaluating large-scale models or machine learning systems.
  • Familiarity with distributed training, large-scale inference, or multi-GPU environments.
  • Publications at leading venues such as NeurIPS, ICML, ICLR, CVPR, CoRL, UAI, JMLR, or TMLR.
  • Strong programming and engineering skills, with the ability to translate research ideas into working implementations.
  • Collaborative, mission-driven mindset and the ability to work effectively across research and engineering teams.

Skills

Reinforcement LearningMachine LearningFoundation ModelsLLMsmultimodal modelsDistributed Traininglarge-scale inferencemulti-gpuPythonPyTorch

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