AI Research Engineer (Agentic Reinforcement Learning)

📋 Description

• Research and develop reinforcement learning algorithms for multimodal models, including
• Design and implement scalable reinforcement learning infrastructure supporting distributed training
• Develop and optimize reward modeling strategies to improve training stability, align model behavior
• Create, curate, and maintain multimodal simulation environments and training datasets to support
• Design and implement rigorous evaluation protocols to measure model performance, monitor progress
• Analyze and optimize policy performance across different modalities by identifying bottlenecks in

🎯 Requirements

• Master's degree in Computer Science or a related discipline. A PhD in Machine Learning, Natural
• Strong track record of AI research, including publications in leading international conferences.
• Demonstrated experience conducting large-scale reinforcement learning experiments in multimodal and
• Proven ability to improve domain-specific decision-making and achieve measurable gains in policy
• Deep understanding of reinforcement learning algorithms and optimization techniques applied to
• Strong knowledge of policy stability, exploration strategies, sample efficiency, and optimization

🎁 Benefits

• Fully Remote Work: Work remotely from anywhere in the world, with a globally distributed team.
• International Collaboration: Collaborate with talented researchers, engineers, and technology
• Cutting-Edge AI Research: Work on advanced reinforcement learning, multimodal architectures
• Research and Innovation: Explore new methodologies and contribute to state-of-the-art developments
• Scientific Recognition: Opportunities to publish research and present findings at leading
• Professional Growth: Develop expertise in emerging AI technologies while contributing to