About this role

Drive innovation in reinforcement learning approaches for advanced models
Optimize decision-making and adaptive behavior for enhanced intelligence
Work across a broad spectrum of systems, including resource-efficient models and complex multi-modal architectures
Develop and implement state-of-the-art reinforcement learning algorithms
Establish clear performance targets and track key performance indicators
Collaborate with cross-functional teams to integrate reinforcement learning agents into production systems

A degree in Computer Science or related field
Ideally PhD in NLP, Machine Learning, or a related field, complemented by a solid track record in AI R&D (with good publications in A* conferences)
Proven experience with large-scale reinforcement learning experiments, including online RL techniques such as Group Relative Policy Optimization (GRPO)
Deep understanding of reinforcement learning algorithms including state-of-the-art online RL methods
Strong expertise in PyTorch and relevant reinforcement learning frameworks
Practical experience in developing RL pipelines
Demonstrated ability to apply empirical research to overcome RL challenges

AI Research Engineer – Reinforcement Learning

Key skills