poolside is hiring for a

Member of Engineering, Pre-training

Position: Full-time, indefinite contract

Location: Remote EMEA/East Coast or Paris

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About poolside

In this decade, the world will create artificial intelligence that reaches human level intelligence (and beyond) by combining learning and search. There will only be a small number of companies who will achieve this. Their ability to stack advantages and pull ahead will determine who survives and wins. 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 and engineering at scale. They will create powerful economic engines. 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.

poolside exists to be one of these companies - to build a world where AI will drive the majority of economically valuable work and scientific progress.

We believe that software development will be the first major capability in neural networks that reaches human-level intelligence because it's the domain where we can combine Search and Learning approaches the best.

At poolside we believe our applied research needs to culminate in products that are put in the hands of people. Today we focus on building for a developer-led increasingly AI-assisted world. We believe that current capabilities of AI lead to incredible tooling that can assist developers in their day to day work. We also believe that as we increase the capabilities of our models, we increasingly empower anyone in the world to be able to build software. We envision a future where not 100 million people can build software but 2 billion people can.

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 pre-training team focused on building out our distributed training of Large Language Models and major architecture changes. This is a hands-on role where you'll be both programming and implementing LLM architectures (dense & sparse) and distributed training code all the way from data to tensor parallelism, while researching potential optimizations (from basic operations to communication) and new architectures & distributed training strategies. You will have access to thousands of GPUs in this team.

Your mission

To train the best foundational models for source code generation in the world in minimum time and with maximum hardware utilization.

Responsibilities

Follow the latest research on LLMs and source code generation. Propose and evaluate innovations, both in the quality and the efficiency of the training.
Do LLM-Ops: babysitting and analyzing the experiments, iterating.
Write high-quality Python, Cython, C/C++, Triton, CUDA 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
Knowledge/Experience with cutting-edge training tricks
Knowledge/Experience of distributed training
Trained LLMs from scratch
Coded LLMs from scratch
Knowledge of deep learning fundamentals

Strong machine learning and engineering background
Research experience

Author of scientific papers on any of the topics: applied deep learning, LLMs, source code generation, etc. - is a nice to have
Can freely discuss the latest papers and descend to fine details
Is reasonably opinionated

Programming experience

Linux
Strong algorithmic skills
Python with PyTorch or Jax
C/C++, CUDA, Triton
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