Continual Learning Researcher

Job Summary

To drive the advancement of continual learning systems, the full-time Continual Learning Researcher will build and evaluate methodologies for turning agent trajectories and model updates into new tasks while collaborating with external partners, working remotely or from locations such as San Francisco, London, or New York.

Key responsibilities

• Develop methods for selective consolidation, replay, adaptation, and reinforcement learning
• Build task-generation and training pipelines with reproducible data to trace regressions
• Conduct experiments to measure skill retention, transfer, and regression across changing tasks

Required qualifications

• Experience in continual or online learning, reinforcement learning, or adaptive production machine learning
• Hands-on experience with model-training and evaluation experimental loops
• Strong Python skills with the ability to create artifacts for research and engineering use
• Demonstrated experimental judgment with a focus on meaningful baselines and clear failure attribution
• Ability to manage ambiguous problems and communicate effectively with partners and teammates