AI Research Scientist

• Conduct end-to-end research and engineering initiatives to advance post-training of agentic and tool-use models to achieve SOTA results.
• Drive broad, cross-cutting model improvements, including factuality, instruction adherence, tool/function use, multi-agent coordination, and reasoning calibration.
• Design and enhance large-scale post-training systems, including data pipelines, training workflows, evaluation frameworks, and benchmark infrastructure.
• Develop rigorous evaluation suites and diagnostic tools to assess model readiness for deployment.
• Strengthen feedback loops from real-world product usage, incorporating both explicit and implicit user signals into post-training.
• Collaborate with tooling, product, and training teams to improve the usefulness, reliability, and agentic capabilities of frontier models.
• Closely liaise with research, engineering and cross-functional teams to determine which integrations are production-ready for inclusion in major model releases.

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AI Research Engineer – Agentic Post-training