About the company
Hyperbolic Labs is on a mission to democratize AI by breaking down the barriers to computing power with our Open-Access AI Cloud. By making better use of idle computing resources across the globe, we offer an innovative GPU marketplace and AI inference service that promise affordability and accessibility for all. As pioneers at the intersection of AI and open-source technology, we believe in an open future where AI innovation is limited only by imagination, not by access to resources. We're looking for forward-thinking individuals who share our passion for making AI universally accessible, secure, and affordable. Join us in building a platform that empowers innovators everywhere to turn their visionary AI projects into reality. As we prepare for growth with our seed round, backed by industry leaders, our team—led by co-founders with PhDs in AI, Math, and Computer Science—is poised to redefine computing
Job Summary
What You’ll Own
📍Customer benchmarking & coordination 📍Be the technical point-of-contact during trials, running both standardized and custom benchmarks to prove our value. 📍Design and run performance tests 📍Design, run, and analyze benchmarks across customer workloads — including comparisons against AWS, Lambda, and others. 📍Debug and optimize customer trials 📍Diagnose performance issues (GPU utilization, NCCL setup, container configs) and recommend fixes. 📍Reporting & documentation 📍Package results into clear, credible reports and handoffs that make technical findings easy to act on. 📍Maintain benchmarking infrastructure 📍Own and maintain the scripts, containers, and environments used to validate performance across SKUs and setups. 📍Continuous iteration 📍Identify performance gaps, optimize cluster configs, and work with supply and engineering to close the loop.
What We’re Looking For
📍Experience running infra performance tests or ML model benchmarks (training, inference, or both). 📍Strong knowledge of GPU cloud infra — how workloads run, what bottlenecks to watch for, and how configs affect performance. 📍Clear and fast written communication (reports, docs, handoffs). 📍Ability to juggle multiple trials/projects at once. 📍Familiarity with the landscape (AWS, Lambda, CoreWeave, Runpod, etc.).
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