AI research lab building open-source language, audio and agent models
Zyphra is a San Francisco AI company training its own foundation models, with a stack spanning PyTorch, CUDA, Triton, Slurm, Ray and vLLM/SGLang across AWS, Azure and GCP. Electron, Tauri and Qualcomm/Intel signals point to on-device and desktop delivery, while adoption of RAG, Puppeteer and Playwright aligns with active work on agentic systems and retrieval pipelines. Hiring is engineering- and research-heavy with minimal recent velocity.
Zyphra is a privately held AI company headquartered in San Francisco, California, with 51–200 employees. It describes itself as a full-stack AGI company, covering model research, large-scale training, inference and end-user applications. Current work spans open-source text-to-speech and audio models, agentic systems with secure execution runtimes, and retrieval pipelines over structured and unstructured data. The team operates multi-cloud GPU infrastructure and engages a developer community through open-source releases and Hugging Face. Hiring is focused in the United States.
Zyphra uses PyTorch, CUDA and Triton for training, Slurm, Ray and Kubernetes for orchestration, vLLM and SGLang for inference, and Terraform and Ansible across AWS, Azure and GCP, plus React, TypeScript, Electron and Tauri.
Projects include large-scale audio training runs, open-source text-to-speech and audio models, agentic systems with secure virtualized runtimes, RAG backends, and search and retrieval pipelines.
Yes, open roles are concentrated in engineering and research, mostly mid-level, all based in the United States, though recent posting velocity is minimal.
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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.