Member of Engineering (Reinforcement Learning)

Experience with Large Language Models (LLM). Deep knowledge of Transformers. Strong deep learning fundamentals. Trained and fine-tuned LLMs from scratch. Extensively used and probed LLMs, familiarity of their capabilities and limitations. Knowledge/Experience of distributed training. Strong machine learning and engineering background. Research experience. Experience in proposing and evaluating novel research ideas. Familiar with, or contributed to the state of the art in at least one of the topics: LLMs, reinforcement learning, source code generation, continual learning. Comfortable in a rapidly iterating environment. Reasonably opinionated. Linux. Strong algorithmic skills. Python with PyTorch or Jax.

Research and experiment on ways to improve reasoning and code generation for LLMs. Own the full experiment life cycle from idea to experimentation and integration. Keep up with latest research, and be familiar with state of the art in LLMs, RL, and code generation. Design, analyze, and iterate on training/fine-tuning/data generation experiments. Write high-quality, pragmatic code. Work in the team: plan future steps, discuss, and always stay in touch.