Principal AI Researcher

What you'll do

• Lead research on world models and learning-based approaches for autonomous networks.
• Develop world models to learn the state and dynamics of large-scale network environments.
• Build models that predict network behavior and the impact of configuration or operational changes.
• Develop model-based reinforcement learning approaches for network optimization, troubleshooting, and remediation.
• Create simulation environments for training and evaluating models before they operate on production networks.
• Explore new methods for representation learning, planning, and sequential decision-making in network environments.
• Develop methods to evaluate the reliability and safety of learned policies before deployment.
• Publish research at leading AI/ML conferences and contribute to open-source projects.

What we're looking for

• Master's degree in Computer Science, Machine Learning, AI, Robotics, Autonomous Systems, or a related field.
• 8+ years of relevant research experience or equivalent demonstrated research impact.
• Research experience in world models, reinforcement learning, model-based RL, representation learning, planning, or sequential decision-making.
• 3+ years of hands-on experience building, training, and optimizing deep learning models using PyTorch, JAX, or comparable frameworks.
• Experience with at least two models trained and evaluated at production or research scale.
• Demonstrated track record of research through publications at leading AI/ML conferences or equivalent contributions.
• Ability to take a research problem from an initial idea through experimentation to a working prototype.