Foundation model developer building AI software agents for enterprises
Poolside trains its own foundation models aimed at enterprise software agents, running a deep-learning stack of PyTorch, JAX, vLLM, Triton, CUDA and NCCL across GCP, AWS and Azure. Hiring tilts heavily toward engineering and data roles, and the project list centers on pretraining data: synthetic dataset generation, deduplicating web crawls and petabyte-scale streaming ingestion. That points to a team whose main bottleneck is data quality and throughput, not model serving.
Poolside is a San Francisco-based, privately held AI company founded in 2023 that develops foundation models for enterprise use, with software agents as its first focus. The company employs 51–200 people and hires in the United States and Indonesia. Its infrastructure spans multiple clouds (GCP, AWS, Azure) and is managed with Kubernetes, Terraform, Ansible and ArgoCD, with Bazel and Buildkite for builds. Observability runs on Grafana, Prometheus and Datadog, while data movement relies on Kafka, Google Cloud Pub/Sub and Apache Spark.
Poolside uses Python, Go, C++ and Cython with PyTorch, JAX, Transformers, vLLM, Triton, CUDA and NCCL, running on GCP, AWS and Azure with Kubernetes, Terraform and ArgoCD.
Current work includes synthetic pretraining data generation, a data ingestion and deduplication system, petabyte-scale streaming, a model factory pipeline, image-input capabilities and a self-serve evaluation platform.
Poolside is headquartered in San Francisco, California, and hires in the United States and Indonesia, mostly for engineering and data roles.
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Poolside's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.