JOB DESCRIPTION
RESPONSIBILITIES
- 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
SKILLS & EXPERIENCE
- Experience with Large Language Models (LLM)
- Deep knowledge of Transformers is a must
- 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
- Is comfortable in a rapidly iterating environment
- Is reasonably opinionated
- Recent academic publications are nice to have
- Programming experience
- Linux
- Strong algorithmic skills
- Python with PyTorch or Jax
- Use modern tools and are always looking to improve
- Strong critical thinking and ability to question code quality policies when applicable
- Prior experience in non-ML programming, especially not in Python - is a nice to have
Salary
Competitive
Monthly based
Location
Worldwide, Worldwide Region, Worldwide
Job Overview
Location
Worldwide, Worldwide Region, Worldwide