Research Engineer / Research Scientist
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 job
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 Learning, Reinforcement Learning, Llm Post-Training, Model Evaluation, Python, PyTorch, TensorFlow, Dataset Creation, Personalization Systems, Agentic AI
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