World Model / Action Policy Researcher(m/w/x)

Requirements

• 5+ years deep learning research experience
• Foundation in representation learning and generative modeling
• Experience with world models and predictive control
• Proficiency in reinforcement learning or imitation learning
• Programming fluency in Python and PyTorch
• Strong experimental and large-scale training skills
• Relevant publications or open-source contributions (plus)
• Ownership, scientific rigor, and clean code
• Performance and scaling mindset
• Curiosity-driven and result-oriented personality
• Interest in interactive environments and simulations
• Experience with Unity, Unreal, or simulators (plus)

Tasks

• Conduct deep learning and reinforcement learning research
• Develop world models using diffusion and transformer architectures
• Design and evaluate policy networks for embodied agents
• Train models to simulate dynamics in learned environments
• Implement research using Python and PyTorch frameworks
• Manage large-scale training and evaluation pipelines
• Oversee projects from initial concept to deployment
• Write clean and reproducible research code
• Optimize research for production and compute efficiency
• Utilize Unity or Unreal Engine for simulations

Work Experience

EducationMore information about education requirement

Languages

Tools & Technologies