HPC Operations Engineer

Lambda, The Superintelligence Cloud, is a leader in AI cloud infrastructure serving tens of thousands of customers. Our customers range from AI researchers to enterprises and hyperscalers. Lambda's mission is to make compute as ubiquitous as electricity and give everyone the power of superintelligence. One person, one GPU. If you'd like to build the world's best AI cloud, join us. *Note: This position requires presence in our San Francisco/San Jose/Bellevue office location 4 days per week; Lambda’s designated work from home day is currently Tuesday. Engineering at Lambda is responsible for building and scaling our cloud offering. Our scope includes the Lambda website, cloud APIs and systems as well as internal tooling for system deployment, management and maintenance. What You’ll Do - Remotely deploy and configure large-scale HPC clusters for AI workloads (up to many thousands of nodes) - Remotely install and configure operating systems, firmware, software, and networking on HPC clusters both manually and using automation tools - Troubleshoot and resolve HPC cluster issues working closely with physical deployment teams on-site - Provide clear and detailed requirements back to other engineering teams on gaps and improvement areas, specifically in the areas of simplification, stability, and operational efficiency - Contribute to the creation of and maintenance of Standard Operating Procedures - Provide regular and well-communicated updates to project leads throughout each deployment - Mentor and assist less experienced team members - Stay up-to-date on the latest HPC/AI technologies and best practices You - Are a deeply experienced HPC engineer comfortable with logical provisioning of a cluster - Have a strong understanding of HPC/AI architecture, operating systems, firmware, software, and networking - 5+ years of experience in deploying and configuring HPC clusters for AI workloads - Have an innate attention to detail - Are in expert in configuring and troubleshooting: - SFP+ fiber, Infiniband (IB), and 100 GbE network fabrics - Ethernet, switching, power infrastructure, GPU direct, RDMA, NCCL, Horovod environments - Linux based compute nodes, firmware updates, driver installation - SLURM, Kubernetes, or other job scheduling systems - Work well under deadlines and structured project plans also knowing when and how to ask for changes to project timelines - Have excellent problem solving and troubleshooting skills - Have flexibility to travel to our North American data centers as on-site needs arise or as part of training exercises - Are able to work independently and as part of a team - Are comfortable mentoring and supporting junior HPC engineers on cluster deployments Nice to Have - Experience with machine learning and deep learning frameworks (PyTorch, Tensorflow) and benchmarking tools (DeepSpeed, MLPerf) - Experience with containerization technologies ( Docker, Kubernetes) - Experience working with the technologies that underpin our cloud business ( GPU acceleration, virtualization, and cloud computing) - Keen situational awareness in customer situations, employing diplomacy and tact - Bachelors degree in EE, CS, Physics, Mathematics, or equivalent work experience Salary Range Information The annual salary range for this position has been set based on market data and other factors. However, a salary higher or lower than this range may be appropriate for a candidate whose qualifications differ meaningfully from those listed in the job description. About Lambda - Founded in 2012, with 500+ employees, and growing fast - Our investors notably include TWG Global, US Innovative Technology Fund (USIT), Andra Capital, SGW, Andrej Karpathy, ARK Invest, Fincadia Advisors, G Squared, In-Q-Tel (IQT), KHK & Partners, NVIDIA, Pegatron, Supermicro, Wistron, Wiwynn, Gradient Ventures, Mercato Partners, SVB, 1517, and Crescent Cove - We have research papers accepted at top machine learning and graphics conferences, including NeurIPS, ICCV,