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Research Engineer / Research Scientist

295k – 555kSan Francisco, CAML EngineeringHybrid7+ YOE
Summary

Research and develop improvements to models' personalization and agentic capabilities through reinforcement learning, dataset creation, and post-training methods. Requires strong ML engineering skills and research experience with novel models.

About the role

Responsibilities

  • Own and pursue a research agenda to improve the proactivity and ability of our models to further user goals
  • Build robust evaluations for tracking modeling improvements
  • Design, implement, test, and debug code across our research stack
  • Collaborate closely with the other research and product teams to influence the shape of technical solutions in the product

Requirements

  • Strong ML engineering skills and research experience, especially with novel and highly capable models
  • Deep understanding of machine learning and machine learning applications
  • Working knowledge of LLM post-training and evaluation approaches
  • Passionate about, or have experience thinking about, personalization and enabling users to achieve their goals
  • Comfortable diving into a large ML codebase to debug
  • Thrive in a dynamic and technically complex environment

Nice-to-Haves

  • Passionate about product-driven research
Skills
Machine LearningReinforcement LearningLLM Post-TrainingModel EvaluationPythonPyTorchTensorFlowDataset CreationPersonalization SystemsAgentic AI
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