Research Scientist 4 - Machine Learning and Inference Research (LLM Post-Training)
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The role
Lead research on post-training LLMs for downstream tasks, focusing on RL-based methods (RLHF, RLVR) and related improvements (reasoning, alignment, distillation).
Design, run, and evaluate experiments to enhance performance, memory, calibration, and tool usage in deployed models.
Collaborate across cross-functional teams to translate research into scalable, real-world impact and inform product decisions.
Publish at top venues, present at conferences, and mentor interns while sustaining an open culture of innovation.
Develop and articulate a coherent research agenda, communicate findings to diverse audiences, and guide adoption of new methods.
Contribute to elevating the broader organization by sharing knowledge and fostering lasting collaborations.
Design, run, and evaluate experiments to enhance performance, memory, calibration, and tool usage in deployed models.
Collaborate across cross-functional teams to translate research into scalable, real-world impact and inform product decisions.
Publish at top venues, present at conferences, and mentor interns while sustaining an open culture of innovation.
Develop and articulate a coherent research agenda, communicate findings to diverse audiences, and guide adoption of new methods.
Contribute to elevating the broader organization by sharing knowledge and fostering lasting collaborations.
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