Deep Agentic Reasoning Engineer (Lorenz Labs)

This role involves designing and evaluating multimodal reasoning models using state-of-the-art deep learning techniques, with a focus on transformer architectures, reinforcement learning, and agentic systems for advanced AI applications.

• Develop multimodal reasoning models
• Implement transformer-based architectures
• Apply reinforcement learning techniques
• Evaluate and refine models
• Collaborate on AI research publications

The technical environment includes deep learning frameworks like PyTorch and TensorFlow, with a focus on transformer models, multimodal data processing, reinforcement learning, and model distillation for AI research and development.

The ideal candidate is a PhD-level AI researcher with expertise in transformer-based multimodal reasoning models, reinforcement learning, and model distillation. They have a strong publication record and experience with agentic reasoning frameworks, capable of leading cutting-edge AI research projects.