Data Center Infrastructure Technician
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Job Description
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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 Plano, TX Data Center 5 days; shift work
What You'll Do
Ensure new server, storage and network infrastructure is properly racked, labeled, cabled, and configured
Troubleshoot hardware and software issues in some of the world’s most advanced systems
Document data center layout and network topology in DCIM software
Work with supply chain & manufacturing teams to ensure timely deployment of systems and project plans for large-scale deployments
Manage a parts depot inventory and track equipment through the delivery-store-stage-deploy-handoff process in each of our data centers
Work closely with HW Support team to ensure data center infrastructure-related support tickets are resolved
Work with RMA team to ensure faulty parts are returned and replacements are ordered
Follow installation standards and documentation for placement, labeling, and cabling to drive consistency and discoverability across all data centers
You
Are familiar with critical infrastructure systems supporting data centers, such as power distribution, air flow management, environmental monitoring, capacity planning, DCIM software, structured cabling, and cable management
Are someone who pays attention to detail and has the ability to follow instructions
Are action-oriented and have a strong willingness to learn
Are willing to travel for bring up of new data center locations
Nice to Have
Experience with troubleshooting server hardware
Experience with/or knowledge of network topology
Familiarity with ticketing systems like JIRA and Zendesk
Experience with Linux administration
Experience with working in large-scale distributed data center environments
Experience with Supermicro & Nvidia hardware
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Lambda
View Company ProfileLambda (operating under lambda.ai, formerly Lambda Labs) is the premier, enterprise-grade AI computing platform, modular AI factory pioneer, and GPU infrastructure powerhouse engineered to operate as the definitive, high-velocity compute backbone for the world’s most advanced AI research labs, engineering teams, and superintelligence initiatives. Founded in 2012 by ML engineers, the company completely eliminates the severe systemic friction of modern AI training—where high-performance model development is often throttled by limited GPU accessibility, complex cluster orchestration, and inefficient interconnect bottlenecks—by deploying an advanced, purpose-built AI factory matrix. Moving far beyond traditional, general-purpose cloud providers, Lambda natively unifies high-density, liquid-cooled, and InfiniBand-interconnected GPU compute infrastructure with a curated, AI-optimized software stack (Lambda Stack). The ecosystem offers a tiered deployment model: on-demand GPU instances for rapid prototyping, \"1-Click Clusters\" for production-ready model training (16 to 2,000+ NVIDIA B200 or H100 GPUs), and bespoke \"Superclusters\" (4,000 to 165,000+ GPUs) designed for foundation model training at gigawatt scale. Trusted by 97% of top U.S. research universities and a massive global footprint of enterprise AI developers, Lambda’s infrastructure is explicitly tuned for PyTorch, TensorFlow, and JAX workloads. Backed by $480M+ in Series D funding and recognized as a key NVIDIA partner for healthcare and supercomputing, the organization maintains a strict \"AI-only\" engineering focus, providing 24/7 technical support specifically centered on resolving complex ML cluster performance, networking, and throughput issues. What sets Lambda apart is its uncompromising dedication to replacing complex, fragmented infrastructure management with absolute compute accessibility and performance predictability; by bridging the gap between mission-critical hardware engineering and the rapid-fire requirements of AI reasoning and generation, the enterprise remains the definitive, category-defining cornerstone of modern algorithmic supercomputing and worldwide AI transformation.
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