
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.
🕒 January 23
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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.
• Research and develop techniques to optimize inference performance for large neural networks. • Improve latency, throughput, memory efficiency, and cost per inference. • Design and evaluate model-level optimizations (quantization, pruning, KV-cache optimization, architecture-aware simplifications). • Implement systems-level optimizations (dynamic batching, kernel fusion, multi-GPU inference, prefill vs decode optimization). • Benchmark inference workloads across hardware accelerators. • Collaborate with engineering teams to deploy optimized inference pipelines. • Translate research insights into production-ready improvements.
• Strong background in machine learning, deep learning, or AI systems. • Hands-on experience optimizing inference for large-scale models. • Proficiency in Python and modern ML frameworks (e.g., PyTorch). • Experience with inference tooling (e.g., Triton, TensorRT, vLLM, ONNX Runtime). • Ability to design experiments and communicate results clearly.
• Health insurance • Flexible work arrangements • Professional development opportunities
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