Featherless AI
1 - 10 employees
Founded 2023
🤖 Artificial Intelligence
☁️ SaaS
🔌 API
Artificial Intelligence • SaaS • 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.
AI Researcher – AI Architecture Research
Job not on LinkedIn
🕒 January 23
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Featherless AI
1 - 10 employees
Founded 2023
🤖 Artificial Intelligence
☁️ SaaS
🔌 API
Artificial Intelligence • SaaS • 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.
📋 Description
• Research and design novel AI architectures (e.g. alternatives to standard Transformer designs, long-context models, efficient sequence modeling, hybrid architectures) • Explore architectural improvements for scalability, efficiency, and stability • Prototype and evaluate new architectures through ablations, benchmarks, and empirical studies • Author and co-author research papers for top ML conferences and journals • Collaborate with engineering teams to translate research into training and inference systems • Stay current with state-of-the-art research and identify promising directions early
🎯 Requirements
• Strong background in machine learning research, with a focus on model architecture • Publication record in ML/AI venues (e.g. NeurIPS, ICML, ICLR, COLM, ACL, EMNLP, arXiv) • Deep understanding of: • Neural network architectures • Sequence models and attention mechanisms • Training dynamics and optimization • Hands-on experience with PyTorch or JAX • Ability to reason rigorously, design clean experiments, and communicate results clearly • Comfortable working in a fast-moving startup environment • Experience with non-Transformer architectures (e.g. RNN-based, state-space, hybrid models) • Work on long-context or memory-efficient models • Open-source research contributions • Experience bridging research and production systems • Background in efficient training or inference-aware architecture design
🏖️ Benefits
• High ownership over research direction and roadmap • Clear path to publishing impactful work • Tight feedback loop between research and real-world deployment • Small, highly technical team with strong research culture • Competitive compensation and meaningful equity
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