Machine Learning (NAVER CLOUD AI)

Job description of AI and ML research of NAVER AI Lab

Machine Learning (@NAVER AI Lab)


Publication at top AI venues and contribution to NAVER and AI communities through impactful research


  • Research intern (remote work available): OO

Research topics (Including, but not limited to)

  • Next generation of backbones for image, video, and audio recognition.
    • Novel neural architecture design (e.g., NAS).
    • Object recognition (e.g., classification, detection, segmentation, retrieval, etc.).
    • Lightweight and energy-efficient models (e.g., pruning, quantization, compression).
    • Learning with large-scale insufficient annotations (e.g., weakly- / self- / semi-supervised learning).
    • Novel learning algorithms for NNs (e.g., normalization, optimization, etc.).
  • Generative models for image, video, text, and audio.
    • Uncoditional & conditional image generation
    • Image-to-image and vid-to-vid translation
    • Disentanglement and controllability
    • Cross-modal generation
    • Audio and music generation
    • Effective learning algorithm for generative models
    • Style transfer and superresolution for images and videos
    • Neural render and superresolution
  • Hyper-scale language models and their extensions.
    • Controllable LM.
    • Multimodality extension.
    • New evaluation metrics and protocols
    • Extension to dialogs, QA, summarization, content generation, etc.
  • Human computer interaction and interactive AI.
    • Accessibility
    • Computational Interaction
    • Computational Social Science and Social Computing
    • Data-driven Interface Design
    • Human Computation
    • Visualization
  • Representation learning for semi-structed or structured data.
    • Graph representation learning
    • Time-series prediction and representation learning
  • Trustworthy AI.
    • Explainable AI and causal inference.
    • Robust machine learning (adversarial robustness, domain generalization).
    • De-biased and fair machine learning.
    • Proper uncertainty estimation (e.g. prediction calibration, probabilistic machine learning).
    • Privacy-preserving AI (e.g. differential privacy, federated learning, etc.).
  • Audio recognition.
    • Automatic speech recognition (ASR).
    • Audio-visual speech recognition.
  • Other topics.
    • Healthcare AI.
    • AI for social good.


  • Research intern
    • Experience on research collaborations and paper writing in related fields.
    • Proficient programming skills in Python (PyTorch).
    • Preferred
      • Currently in an MS or PhD programme in CS, EE, mathematics or other related technical fields.
      • Proficient track record of publications at top-tier conferences in machine learning, computer vision, natural language processing, audio, hci, and speech.

Application process

  • Research intern
    • Algorithm coding test (more than two).
    • Job interviews (more than one).
  • If you are interested,