Member of Technical Staff - Post-Training

• Build systems that transform powerful pre-trained models into aligned and general agents.
• Drive research and engineering initiatives that push the frontier of post-training, from data curation to large-scale optimization.
• Develop data generation pipelines, reward models, reinforcement learning algorithms, and inference-time scaling techniques.
• Collaborate across pre-training and post-training teams to deliver step-function gains in model capability.
• Contribute to shaping our understanding of how large models learn to reason, follow instructions, and improve through reinforcement learning.
• Deep understanding of machine learning fundamentals and practical experience with large-scale LLM training.
• Strong engineering skills, comfortable diving into complex ML codebases and distributed systems.
• Experience improving model behavior through data, reward modeling, or RL techniques.
• Evidence of owning ambitious research or engineering agendas that led to measurable model improvements.
• Thrive in a fast-paced, high-agency startup environment; bias toward action and clarity of execution.
• Able to work fluidly across research and infra boundaries
• Strong communication capabilities and comfort working collaboratively
• Passionate about advancing the frontier of intelligence.

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