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    <job>
      <externalid>e53014e6-57c</externalid>
      <Title>Data Center Engineer, Resource Efficiency – Compute Supply</Title>
      <Description><![CDATA[<p>As a Power &amp; Resource Efficiency Engineer, you&#39;ll sit at the intersection of IT and facilities , building the systems, models, and control loops that optimize how we allocate and consume power, cooling, and physical capacity across our TPU/GPU fleet.</p>
<p>You&#39;ll own the technical strategy for turning raw data center capacity into reliable, efficient compute, working across power topology, workload scheduling, and real-time telemetry to push utilization as close to the physical envelope as possible while maintaining our availability commitments.</p>
<p>Key responsibilities include:</p>
<ul>
<li>Building models that forecast consumption across electrical and mechanical subsystems, informing capacity planning, energy procurement, oversubscription targets and risks, including statistical modeling of cluster utilization, workload profiles, and failure modes.</li>
</ul>
<ul>
<li>Designing IT/OT interfaces that bridge compute orchestration with facility controls, enabling real-time telemetry across accelerator hardware, power distribution, cooling, and schedulers.</li>
</ul>
<ul>
<li>Building and operating load management systems that use power and cooling topology to enable load management and power/thermal-aware placement to maximize throughput while meeting SLOs.</li>
</ul>
<ul>
<li>Partnering with data center providers to drive design optimizations and hold them accountable to SLA-grade performance standards, providing technical diligence on partner architectures.</li>
</ul>
<p>In this role, you&#39;ll need to have deep knowledge of data center power distribution and cooling architectures, and how they interact with IT load profiles. Experience with reliability engineering, SLA development, and failure-mode analysis is also essential.</p>
<p>Additionally, proficiency in statistical modeling and simulation for infrastructure capacity or power utilization, familiarity with SCADA/BMS/EPMS, telemetry pipelines, and control systems, and exposure to accelerator deployments and their power management interfaces are highly desirable.</p>
<p>This is a challenging and rewarding role that requires a unique blend of technical expertise, business acumen, and collaboration skills. If you&#39;re passionate about data center infrastructure, AI, and sustainability, we encourage you to apply.</p>
<p style="margin-top:24px;font-size:13px;color:#666;">XML job scraping automation by <a href="https://yubhub.co">YubHub</a></p>]]></Description>
      <Jobtype>full-time</Jobtype>
      <Experiencelevel>senior</Experiencelevel>
      <Workarrangement>hybrid</Workarrangement>
      <Salaryrange>$320,000-$405,000 USD</Salaryrange>
      <Skills>data center power distribution and cooling architectures, _SYSTEMS, reliability engineering, SLA development, failure-mode analysis, statistical modeling and simulation, SCADA/BMS/EPMS, telemetry pipelines, control systems, accelerator deployments, power management interfaces, Python, similar languages, control theory, dynamical systems, cyber-physical systems design, energy storage, microgrid integration, demand response, behind-the-meter generation</Skills>
      <Category>Engineering</Category>
      <Industry>Technology</Industry>
      <Employername>Anthropic</Employername>
      <Employerlogo>https://logos.yubhub.co/anthropic.com.png</Employerlogo>
      <Employerdescription>Anthropic creates reliable, interpretable, and steerable AI systems. It operates at massive scale, with a focus on extracting maximum compute throughput from every watt.</Employerdescription>
      <Employerwebsite>https://www.anthropic.com/</Employerwebsite>
      <Compensationcurrency></Compensationcurrency>
      <Compensationmin></Compensationmin>
      <Compensationmax></Compensationmax>
      <Applyto>https://job-boards.greenhouse.io/anthropic/jobs/5159642008?utm_source=yubhub.co&amp;utm_medium=jobs_feed&amp;utm_campaign=apply</Applyto>
      <Location>Remote-Friendly, United States</Location>
      <Country></Country>
      <Postedate>2026-04-18</Postedate>
    </job>
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