Research Engineer, Production Model Post-Training
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The role
Implement and optimize post-training techniques at scale on frontier language models to improve production safety, alignment, and performance.
Conduct research to develop post-training recipes, including Constitutional AI and RLHF, that directly enhance model quality.
Design, build, and run robust pipelines for fine-tuning and evaluating models across diverse metrics.
Develop tools to measure, monitor, and debug model training and deployment in large-scale distributed systems.
Collaborate with research and engineering teams to translate cutting-edge techniques into production-ready implementations and establish best practices for reliability.
Balance research exploration with engineering rigor, maintain clarity under time pressure, and contribute to safe, responsible AI deployment.
Conduct research to develop post-training recipes, including Constitutional AI and RLHF, that directly enhance model quality.
Design, build, and run robust pipelines for fine-tuning and evaluating models across diverse metrics.
Develop tools to measure, monitor, and debug model training and deployment in large-scale distributed systems.
Collaborate with research and engineering teams to translate cutting-edge techniques into production-ready implementations and establish best practices for reliability.
Balance research exploration with engineering rigor, maintain clarity under time pressure, and contribute to safe, responsible AI deployment.
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