Member of Technical Staff - Research, Post-Training

Highlights

• Build platform covering full LLM lifecycle from training to production observation.
• Advance post-training for long-context and long-horizon real-world tasks.
• Improve inference efficiency and reliability for high-stakes deployments.

What they offer

• Equity

Ideal candidate

Mission-driven researcher with RL and foundation-model depth who wants to turn advances into real product impact and collaborate across research and engineering.

Requirements

• PhD in CS, ML or related field, or master's with significant research or industry experience
• Record of research accomplishments in RL, ML, foundation models or related fields
• Experience with large-scale training and inference infrastructure including distributed systems and multi-node GPU clusters
• Experience developing, training, optimizing or deploying state-of-the-art large-scale models
• First-author publications at venues such as NeurIPS, ICML, ICLR, CoRL, CVPR, UAI, JMLR or TMLR
• Mission-driven mindset focused on translating research into product impact
• Collaborative spirit and ability to work across research and engineering teams