Join to apply for the Machine Learning Engineer - Model Performance role at inference.net
Join to apply for the Machine Learning Engineer - Model Performance role at inference.net
Inference.net is seeking a Machine Learning Engineer to join our team, focusing on optimizing the performance of our cutting-edge AI inference systems. This role involves working with state-of-the-art large language models and ensuring they run efficiently and effectively at scale. You will be responsible for deploying state-of-the-art models at scale and performing optimizations to increase throughput and enable new features. This position offers the chance to collaborate closely with our engineering team and make significant contributions to open source projects, like SGLang and vLLM.
About Inference.net We are building a distributed LLM inference network that combines idle GPU capacity from around the world into a single cohesive plane of compute that can be used for running large-language models like DeepSeek and Llama 4. At any given moment, we have over 5,000 GPUs and hundreds of terabytes of VRAM connected to the network. We are a small, well-funded team working on difficult, high-impact problems at the intersection of AI and distributed systems. We primarily work in-person from our office in downtown San Francisco. Our investors include A16z CSX and Multicoin. We are high-agency, adaptable, and collaborative. We value creativity alongside technical prowess and humility. We work hard, and deeply enjoy the work that we do. ResponsibilitiesReferrals increase your chances of interviewing at inference.net by 2x
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