Job description
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.
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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 in our pre-training team focused on building out our distributed training and inference of Large Language Models (LLMs). This is a hands-on role that focuses on software reliability and fault tolerance. You will work on cross-platform checkpointing, NCCL recovery, and hardware fault detection. You will make high-level tools. You will not be afraid of debugging Linux kernel modules. You will have access to thousands of GPUs to test changes.
Strong engineering skills are a prerequisite. We assume good knowledge of Torch, NVIDIA GPU architecture, reliability concepts, distributed systems, and best coding practices. A basic understanding of LLM training and inference principles is required. We look for fast learners who are prepared for a steep learning curve and are not afraid to step out of their comfort zone.
YOUR MISSION
To help train the best foundational models for source code generation in the world
RESPONSIBILITIES
Identify, study, and troubleshoot hardware problems during training at scale
Minimize the GPU idle time during faults, both operationally and strategically
Design and develop tools and add-ons to accelerate the training recovery
Improve the performance and reliability of checkpointing
Write high-quality Python (PyTorch), Cython, C/C++, CUDA API code
SKILLS & EXPERIENCE
Understanding of Large Language Models (LLM)
Basic knowledge of Transformers
Knowledge of deep learning fundamentals
Strong engineering background
Programming experience
Linux API, Linux kernel
Strong algorithmic skills
Python with numpy, PyTorch, or Jax
C/C++
NCCL
Use modern tools and are always looking to improve
Strong critical thinking and ability to question code quality policies when applicable
Distributed systems
Reliability
Observability
Fault-tolerance
K8s stack
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 Eiso, our CTO & Co-Founder
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
