Member of Technical Staff — Agent Post-Training

Moonlake AI is building the frontier of interactive world models, focusing on systems that generate and reason over 3D environments for robotics and embodied AI. The Member of Technical Staff will lead reinforcement learning infrastructure and model post-training, working closely with the research team to improve large agents through various advanced training methodologies.

Responsibilities:

• Build RL and post-training pipelines for multimodal, vision-language, and code-generating agents
• Develop infrastructure for supervised fine-tuning, preference optimization, reward modeling, and reinforcement learning
• Create systems for collecting, filtering, replaying, and learning from agent trajectories
• Design rewards, verifiers, and evaluations for long-horizon agent tasks
• Improve agents’ ability to plan, write and execute code, use tools, recover from errors, and complete complex workflows
• Scale distributed training and high-throughput rollout generation across multi-GPU environments
• Improve training reliability, reproducibility, observability, and cost efficiency
• Help define Moonlake’s long-term strategy for agent, robotics, and embodied-model training