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A leading AI research company is seeking a skilled engineer to join their pre-training team. The role involves working on distributed training and inference of Large Language Models, requiring strong programming skills in Python and C/C++. This position offers fully remote work, flexible hours, and a supportive and inclusive company culture.
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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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.
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 development best practices, maintenance, and code architecture. You will have access to thousands of GPUs to verify changes.
Strong engineering skills are a prerequisite. We assume perfect knowledge of CI/CD, reliability concepts, software architecture, and code quality properties. 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.
To help train the best foundational models for source code generation in the world