Full-stack AGI company building open-source language models and agentic systems
Zyphra is an AI research and product company focused on large-scale model training, RAG systems, and agentic runtimes. The stack—PyTorch, vLLM, Ray, Pinecone, Weaviate—reflects deep infrastructure work; active adoption of RAG, Puppeteer, and Playwright across projects signals a shift toward retrieval-augmented and agent-driven capabilities. The hiring mix skews research and engineering (12 of 14 open roles), with intentional depth in mid-level and lead positions, suggesting they're scaling model development and backend systems in parallel.
Zyphra builds full-stack AGI technology from model training through deployment. The company is actively working on large-scale audio and language model training, search and retrieval pipelines, open-source text-to-speech models, agentic systems, and secure execution runtimes for agents. Infrastructure includes orchestration (Kubernetes, Slurm), distributed compute frameworks (Spark, Beam, Ray), and cloud-native tooling across AWS, Azure, and GCP. They are based in San Francisco with 51–200 employees and are currently hiring across the United States.
Core stack: PyTorch, Python, vLLM, Ray, Kubernetes, Slurm. Data layer: FAISS, Weaviate, Pinecone, Apache Spark, Beam. Infrastructure: AWS, Azure, GCP, Docker, Terraform. Actively adopting RAG, Puppeteer, Playwright.
Large-scale audio and language model training, search/retrieval pipelines, open-source text-to-speech models, agentic systems, agent execution runtimes, observability systems, and RAG backends. Focus areas include community growth and increasing open-source adoption.
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Zyphra'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.