As a full-stack product engineer, you will own the development of product surfaces for model training, ensuring usability and scalability for researchers and engineers.
You will design and build data and analytics systems to enhance model research, collaborating closely with researchers to optimize workflows and improve training efficiency.
Lead the development of multimodal capabilities at Poolside, focusing on image input to enhance software engineering and general agent functionalities.
Build a reliable, scalable Experiment Platform that integrates research systems and enhances model development at Poolside.
Optimize GPU utilization and enhance inference serving for Poolside's researchers by developing scheduling systems and collaborating with cross-functional teams.
Design and implement the build, CI/CD, and tooling infrastructure to enhance the developer experience for Poolside's researchers and engineers.
Join the Platform engineering team to design and develop a secure, reliable, and performant sandboxed execution environment for agent research and product development.
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.
Staying in sync with the latest research in the fields of dataset design and pretraining is key to success in this role. You will constantly lead original research initiatives through short, time-bounded experiments while deploying highly.
The problems here are genuinely hard and the surface area is wide. One day you're digging deep to understand how developers experience a new agentic workflow; the next you're building a proof-of-concept that changes the direction of a.
This role involves working on the Applied Research team to transform pre-trained LLMs into effective AI systems for coding and software development.
Design and implement a scalable self-serve evaluation platform to enhance research and development, enabling efficient evaluation processes for the team.
Design and implement infrastructure and tooling for evaluations and benchmarks, collaborating with research and product teams to enhance user experience.
As a core member of the Pretraining Data team, you will architect and maintain high-performance pipelines to transform vast amounts of raw data into high-quality datasets for model training.
This role focuses on improving the quality of datasets for training models, generating synthetic data at scale, and collaborating across teams to enhance model capabilities.
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