ABOUT POOLSIDE

In this decade, the world will create Artificial General Intelligence. There will only be a small number of companies who will achieve this. Their ability to stack advantages and pull ahead will define the winners. These companies will move faster than anyone else. They will attract the world's most capable talent. They will be on the forefront of applied research, engineering, infrastructure and deployment at scale. They will continue to scale their training to larger & more capable models. They will be given the right to raise large amounts of capital along their journey to enable this. They will create powerful economic engines. They will obsess over the success of their users and customers.

poolside exists to be this company - to build a world where AI will be the engine behind economically valuable work and scientific progress.

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ABOUT OUR TEAM

We are a remote-first team that sits across Europe and North America and comes together once a month in-person for 3 days and for longer offsites twice a year.

Our R&D and production teams are a combination of more research and more engineering-oriented profiles, however, everyone deeply cares about the quality of the systems we build and has a strong underlying knowledge of software development. We believe that good engineering leads to faster development iterations, which allows us to compound our efforts.

ABOUT THE ROLE

You would be working on our reinforcement learning team focused on improving reasoning and coding abilities of Large Language Models through reinforcement learning. This is a hands-on role where you'll work end-to-end from researching new exploration or training algorithms, to designing and scaling up RL environments, to implementing your ideas across the stack. You will have access to thousands of GPUs in this team.

YOUR MISSION

To push the frontier of reasoning and coding capabilities of foundational models.

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

PROCESS

• Intro call with one of our Founding Engineers

• Technical Interview(s) with one of our Founding Engineers

• Team fit call with the People team

• Final interview with one of our Founding Engineers

BENEFITS

• Fully remote work & flexible hours

• 37 days/year of vacation & holidays

• Health insurance allowance for you and dependents

• Company-provided equipment

• Wellbeing, always-be-learning and home office allowances

• Frequent team get togethers

• Great diverse & inclusive people-first culture