Job Description

Responsibilities: Design, train, and optimize Large Language Models (LLMs) from scratch. Scale distributed training on massive GPU clusters (500+ H100 GPUs). Implement advanced reinforcement learning techniques (RLHF, adversarial self-play, real-time control). Develop high-performance architectures for multi-modal AI systems. Build simulation environments for RL agents. Optimize inference speed and deployment efficiency. Your Profile: Deep expertise in LLMs; you've built and trained large-scale models yourself. Experience with large-scale distributed training on 500+ GPU superclusters. Deep understanding of reinforcement learning, neural network optimization, and self-play methods. Expertise in PyTorch, TensorFlow, JAX and low-level optimization techniques (CUDA, Triton, DeepSpeed, etc.). Familiarity with high-performance computing (HPC, NVLink, InfiniBand, parallel computing). Strong publication track record in AI/ML research is a plus. Relocation to Jena, Germany after onboarding. Language requirements: German or English.