Kuzco
Senior Distributed ML Systems Engineer
Kuzco, San Francisco, California, United States, 94199
Kuzco is seeking a Senior ML Infrastructure Engineer to join our team. This role involves developing large-scale, fault-tolerant systems that handle millions of large language model inference requests per day. If you are passionate about developing next-generation ML systems that operate at scale, we want to hear from you.About KuzcoWe 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 Llama and Mistral. At any given moment, we have over 5,000 GPUs and hundreds of terabytes of VRAM connected to the network. Learn more
here .We are a small, well-funded team of staff-level engineers who work in-person in downtown San Francisco on difficult, high-impact engineering problems. Everyone on the team has been writing code for over 10 years, and has founded and run their own software companies. 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; we are almost always online at least six days per week.About the RoleYou will be responsible for designing and implementing the core systems that power our globally distributed LLM inference network. You'll work on problems at the intersection of distributed systems, machine learning, and resource optimization.Key ResponsibilitiesDesign and implement scalable distributed systems for our inference networkDevelop models for efficient resource allocation across a network of heterogeneous hardware and quickly changing topologyOptimize network latency, throughput, and availabilityBuild robust logging and metrics systems to monitor network health and performanceConduct reviews of architecture and system design to ensure use of best practicesCollaborate with founders, engineers, and other stakeholders to improve our infrastructure and product offeringsWhat We're Looking ForVery strong problem-solving skills and ability to work in a startup environment5+ years of experience in building high performance systemsStrong programming skills in Typescript, Python, and one of Go, Rust, or C++Solid understanding of distributed systems conceptsKnowledge of orchestrators and schedulers like Kubernetes and NomadUse of AI tooling in development workflow (ChatGPT, Claude, Cursor, etc)Experience with LLM inference engines like vLLM or TensorRT-LLM is plusExperience with GPU programming and optimization (CUDA experience is a plus)CompensationWe offer competitive compensation, equity in a high-growth startup, and comprehensive benefits. The base salary range for this role is $180,000 - $250,000, plus equity and benefits, depending on experience.Equal OpportunityKuzco is an equal opportunity employer. We welcome applicants from all backgrounds and don't discriminate based on race, color, religion, gender, sexual orientation, national origin, genetics, disability, age, or veteran status.If you're excited about building the future of developer-first AI infrastructure, we'd love to hear from you. Please send your resume, LinkedIn, and GitHub to sam@kuzco.xyz.
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here .We are a small, well-funded team of staff-level engineers who work in-person in downtown San Francisco on difficult, high-impact engineering problems. Everyone on the team has been writing code for over 10 years, and has founded and run their own software companies. 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; we are almost always online at least six days per week.About the RoleYou will be responsible for designing and implementing the core systems that power our globally distributed LLM inference network. You'll work on problems at the intersection of distributed systems, machine learning, and resource optimization.Key ResponsibilitiesDesign and implement scalable distributed systems for our inference networkDevelop models for efficient resource allocation across a network of heterogeneous hardware and quickly changing topologyOptimize network latency, throughput, and availabilityBuild robust logging and metrics systems to monitor network health and performanceConduct reviews of architecture and system design to ensure use of best practicesCollaborate with founders, engineers, and other stakeholders to improve our infrastructure and product offeringsWhat We're Looking ForVery strong problem-solving skills and ability to work in a startup environment5+ years of experience in building high performance systemsStrong programming skills in Typescript, Python, and one of Go, Rust, or C++Solid understanding of distributed systems conceptsKnowledge of orchestrators and schedulers like Kubernetes and NomadUse of AI tooling in development workflow (ChatGPT, Claude, Cursor, etc)Experience with LLM inference engines like vLLM or TensorRT-LLM is plusExperience with GPU programming and optimization (CUDA experience is a plus)CompensationWe offer competitive compensation, equity in a high-growth startup, and comprehensive benefits. The base salary range for this role is $180,000 - $250,000, plus equity and benefits, depending on experience.Equal OpportunityKuzco is an equal opportunity employer. We welcome applicants from all backgrounds and don't discriminate based on race, color, religion, gender, sexual orientation, national origin, genetics, disability, age, or veteran status.If you're excited about building the future of developer-first AI infrastructure, we'd love to hear from you. Please send your resume, LinkedIn, and GitHub to sam@kuzco.xyz.
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