
51 - 200 employees
Founded 2023
🤖 Artificial Intelligence
🏢 Enterprise
Artificial Intelligence • Enterprise
poolside is a frontier AI lab and enterprise platform that builds and deploys foundation models, multi-agent systems, and developer-facing tools focused on automating complex software work. The company specializes in on-prem and VPC deployments, security-first integrations, governance, and connectors to enterprise data sources so organizations can run agents and models inside their own boundaries. Poolside embeds research and engineering with customers to deliver outcome ownership, risk controls, and measurable business impact while advancing toward AGI by starting in high-consequence software environments.
🕒 January 29
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51 - 200 employees
Founded 2023
🤖 Artificial Intelligence
🏢 Enterprise
Artificial Intelligence • Enterprise
poolside is a frontier AI lab and enterprise platform that builds and deploys foundation models, multi-agent systems, and developer-facing tools focused on automating complex software work. The company specializes in on-prem and VPC deployments, security-first integrations, governance, and connectors to enterprise data sources so organizations can run agents and models inside their own boundaries. Poolside embeds research and engineering with customers to deliver outcome ownership, risk controls, and measurable business impact while advancing toward AGI by starting in high-consequence software environments.
• Build and maintain high-performance pipelines for trillions of tokens. • Deliver diverse and high quality datasets for pre-training foundation models. • Closely work with other teams such as Pretraining, Posttraining, Evals and Product to to ensure alignment on the quality of the models delivered.
• Strong background in building production-grade, distributed data systems for machine learning, with experience in: • Orchestration: Slurm, Airflow, or Dagster • Observability & Reliability: CI/CD, Grafana, Prometheus, etc. • Infra: Git, Docker, k8s, cloud managed services • Batched inference (ex: vLLM) • Performance obsession, especially with large-scale GPU clusters and distributed pipelines • Expert-level python knowledge and ability to write clean and maintainable code • Strong algorithmic foundations • Proficiency with libraries like Polars, Dask, or PySpark • Nice to have: • Experience in building trillion-scale SOTA pretraining datasets • Experience translating research to production at scale • Experience with OCR, web crawling, or evals • Prior experience pre-training LLMs
• 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
Apply Now🕒 January 21
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