About the job
ABOUT POOLSIDE
At Poolside, we are on a mission to pioneer the development of Artificial General Intelligence (AGI) within this decade. Only a select few companies will lead in this endeavor, and we are determined to be among them. Our unique advantage lies in our ability to innovate rapidly, attract top-tier talent, and excel in applied research, engineering, and infrastructure deployment at scale. We are committed to advancing our training capabilities with larger and more sophisticated models while fostering economic growth and ensuring the success of our users and customers.
Poolside is focused on creating a future where AI drives economic advancement and scientific breakthroughs. We believe that accelerating the software development process is key to reaching AGI, achieved by reinventing the developer experience through intelligent systems and coding assistants. Our solutions are deployed directly into the development environments of security-focused enterprises.
ABOUT OUR TEAM
Founded in the US, our team operates remotely across Europe and North America, gathering for in-person collaboration (and delightful croissants) in Paris each month from Monday to Wednesday, with an open invitation to extend the stay for the entire week. We also organize annual off-site retreats.
Our multidisciplinary team combines expertise in research, engineering, and business. What unites us is a shared passion for our collaborative work. We are racing towards our goal, necessitating hard work, intellectual curiosity, and an obsessive focus. To balance this intensity, we have cultivated a team of humble and kind individuals who contribute to the unique culture at Poolside. Together, we build intentionally, creating a compounding effect that propels our mission of achieving AGI through intelligent systems designed for software development.
ABOUT THE ROLE
As the leader of our Data Platform team, you will spearhead the development and maintenance of a robust platform that empowers our Applied Research teams at Poolside to create high-quality datasets for pretraining and post-training, and to conduct extensive experiments from data retrieval to evaluations and benchmarks.
