Senior Research Scientist – Machine Learning for Decision Making and Optimization

About the role

We are seeking a Senior Research Scientist to advance machine‑learning approaches for sequential decision making and combinatorial optimization within our Optimization with Learning team. You will work on real‑world robotics challenges, especially large‑scale robot fleet coordination in dynamic environments.

Key responsibilities

• Lead end‑to‑end research projects on ML methods for decision making and optimization.
• Identify and formulate impactful problems inspired by robotics applications.
• Design and develop new models and algorithms, such as deep reinforcement learning and graph neural networks.
• Oversee prototype and proof‑of‑concept implementation to evaluate novel approaches.
• Publish results in top‑tier conferences and journals and present findings to internal and external audiences.
• Collaborate with engineers across NAVER LABS to transfer research to operational robotic systems.
• Mentor junior researchers and research engineers.
• Enhance team visibility through talks, publications, and collaborations.

Required profile

• PhD in machine learning, optimization, robotics, computer science or a related discipline.
• Strong research track record demonstrated by publications in leading venues.
• Proven ability to lead and drive research projects independently.
• Excellent programming skills in Python and experience with deep‑learning frameworks such as PyTorch.
• Experience designing, implementing, and evaluating machine‑learning models.

Required skills

• Python
• PyTorch
• Deep reinforcement learning
• Graph neural networks
• Machine learning
• Sequential decision making
• Optimization