
1 - 10 employees
Founded 2023
đ€ Artificial Intelligence
âïž SaaS
đ API
Artificial Intelligence âą SaaS âą API
Featherless AI is a serverless AI inference and model hosting provider that offers API access to a large and growing catalog of open-weight models (12,200+), enabling developers and businesses to deploy, fine-tune, and run models at scale without managing servers. The company provides flat subscription pricing with unlimited tokens, GPU orchestration, private/anonymous usage (no logs), and options for enterprise self-hosting or scale units for high concurrency. Featherless AI also operates as an AI research lab focused on open-source and post-transformer model research, claiming significant cost and performance improvements for large models and AI agents.
đ May 15
Account Executive driving sales of AI Cloud solutions for Featherless, engaging with technical buyers and managing complex deals. Join a mission-driven team in a fast-growing AI environment.
đ January 23
AI Researcher focused on training optimization for large-scale model training. Developing techniques to reduce cost, accelerate convergence, and improve model quality.
đ January 23
AI Researcher focusing on multilingual data to scale language models across languages and domains. Collaborating on research execution, data strategies, and publishing high-quality research.
đ January 23
AI Researcher optimizing inference performance for large neural networks in remote global environment. Designing, evaluating, and deploying high-performance inference systems.
đ January 23
AI Researcher focused on distillation techniques for high-performance models. Collaborating on research and productionizing outcomes with a small, highly technical team.
đ January 23
AI Researcher focused on AI architecture research analyzing and advancing next-gen model architectures in a remote global team.
đ January 23
Machine Learning Engineer focusing on AI architecture research and prototyping next-generation models. Collaborating with a small team to influence a Series-A company's technical direction.
đ January 22
ML Engineer focused on training optimization, scaling and improving large-scale model training systems. Collaborating with researchers on model architecture and capability advancement.
đ January 22
Machine Learning Engineer managing and scaling multilingual data pipelines for diverse languages. Collaborating closely with researchers and engineers for robust model performance across cultural contexts.
đ January 22
Machine Learning Engineer optimizing model inference performance at scale, bridging research and production for fast, reliable ML systems.
đ January 22
Machine Learning Engineer specializing in model distillation to create smaller, faster models for production. Engage in cutting-edge research and practical applications in a remote team.