We enable serverless inference via our GPU orchestration and model load-balancing system. We unlock fine-tuning by enabling organizations to size their server fleet to throughput needs, not number of models in the catalogue. See it in action on our public cloud, which offers inference for 10k+ open weight models.
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Featherless gives you the freedom to reliably deploy any open-source AI model effortlessly.
Full company description
We enable serverless inference via our GPU orchestration and model load-balancing system. We unlock fine-tuning by enabling organizations to size their server fleet to throughput needs, not number of models in the catalogue.
See it in action on our public cloud, which offers inference for 10k+ open weight models.
LinkedIn followers
3,737
People associated on LinkedIn
32
Reported office locations
San Francisco, California, US
Business categories
Artificial Intelligence (AI)
Cloud Computing
Database
Other recorded names
Featherless AI
Specialties
AI
Profile identifies a recruitment agency
No
Reported total investment
25,000,000
Currency and observation date were not supplied; this is not a current valuation or a funding round.
Industry
Technology, Information and Internet
Size
2-10 employees
Headquarters
San Francisco, California
Organization type
Privately Held
Year founded
2023
Specialties
AI
Featherless AI has 4 open jobs in Canada as of November 6, 2026. Top locations: Vancouver, Halifax and Ottawa.
3+ YOECandidates need 3 to 6 years in pre-sales engineering, solutions architecture or customer-facing engineering, with hands-on Python and working knowledge of LLM inference serving. Featherless AI also expects familiarity with the open-model ecosystem, containers and Kubernetes, and clear written communication.
1+ YOECandidates need 1-2 years of experience in sales, developer relations or entrepreneurship, and must be comfortable talking with technical people. Featherless AI wants clear written and spoken English, strong AI tool skills and the ability to work independently.
3+ YOECandidates need 3 to 6 years in a closing role in cloud, MLOps or AI tooling, with a record of closing deals with technical buyers. They must communicate clearly, forecast well and be self-driven.
5+ YOECandidates need 5+ years in startup operations, strategy consulting, banking or a similar high-ownership role, with strong judgment under ambiguity. They need enough AI inference and model-serving knowledge to ask good questions, and a record of turning messy problems into finished plans.
Prioritization, Logistics, Recruitment, Sales, Leadership, ML