
Hugging Face
New York, NY
Open-source AI platform for ML models and collaboration
About
Hugging Face builds an open-source platform where the machine learning community collaborates on models, datasets, and applications. It provides libraries like Transformers and tools for developers to build, train, and deploy AI models. The platform democratizes access to state-of-the-art ML through community contributions and shared resources.
Tech stack
Python, AWS, GCP, Kubernetes, Docker, PyTorch, Azure, Hugging Face, pandas, S3, GitHub, TypeScript
Perks & benefits
Health insurance, Dental insurance, Vision insurance, Parental leave, Unlimited PTO, Equity, Flexible hours
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Open jobs
5Own and evolve Hugging Face’s open-source voice-agent stack and bring hf-voice from demo to production. The role requires senior experience with Python, distributed real-time systems, developer infrastructure, and production AI or multimodal models.
Build and operate high-performance, large-scale storage systems (200PB+) for Hugging Face's AI platform. Contribute to open-source Rust xet-core and backend services; requires 8+ years scaling distributed systems with strong low-level programming skills (Rust preferred).
Build and operate low-level, high-performance storage infrastructure at massive scale, contributing to the Rust-based xet-core project and Xet Storage backend. The role requires 8+ years of distributed systems, storage, or networking experience and strong independent execution.
As an Open-Source Machine Learning Engineer, you will enhance the open-source machine learning ecosystem, focusing on libraries like Transformers and PyTorch. You will collaborate with the ML community, contributing to and supporting the tools you build.
Build and improve open-source machine learning libraries while collaborating with researchers, practitioners, users, and contributors. The role requires strong Python, deep-learning framework experience, practical familiarity with the Hugging Face ecosystem, and a public record of open-source contributions.