Data Center Engineer, Resource Efficiency – Compute Supply

About Anthropic

Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

About the Role

Anthropic's AI infrastructure operates at massive scale, and extracting maximum compute throughput from every watt is a first-order priority. As a Power & Resource Efficiency Engineer, you'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. You'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.

What You'll Do

• Build 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.

• Design IT/OT interfaces that bridge compute orchestration with facility controls, enabling real-time telemetry across accelerator hardware, power distribution, cooling, and schedulers.

• Build and operate load management systems that use power and cooling topology to enable load management and power/thermal-aware placement to maximize throughput while meeting SLOs.

• Partner with data center providers to drive design optimizations and hold them accountable to SLA-grade performance standards, providing technical diligence on partner architectures.

What We're Looking For

• 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.

• Proficiency in statistical modeling and simulation for infrastructure capacity or power utilization.

• Familiarity with SCADA/BMS/EPMS, telemetry pipelines, and control systems. Experience building software that bridges IT and OT.

• Exposure to accelerator deployments and their power management interfaces strongly preferred.

• Demand response, grid interaction, or behind-the-meter generation experience is a plus.

• Ability to translate between infrastructure engineering, software teams, and external partners.

Required Qualifications

• Bachelor's degree in Electrical Engineering, Mechanical Engineering, Power Systems, Controls Engineering, or a related field

• 5+ years of experience in data center infrastructure or facility engineering

• Demonstrated experience with data center power distribution and cooling system architectures

• Experience building or operating software-based power management, load scheduling, or control systems

• Proficiency in Python or similar languages for statistical modeling, simulation, or automation of data center infrastructure optimizations

• Familiarity with SCADA, BMS, EPMS, or industrial control systems and associated protocols (Modbus, BACnet, SNMP)

• Track record of cross-functional collaboration across hardware, software, and facilities teams

Preferred Qualifications

• Master's or PhD in Controls, Power Systems, or related discipline and 3+ years of experience in data center infrastructure or facility engineering

• Experience with accelerator-class deployments and their power management interfaces

• Background in control theory, dynamical systems, or cyber-physical systems design

• Experience with energy storage, microgrid integration, demand response, or behind-the-meter generation

• Familiarity with reliability engineering methods

• Experience with SLA development, availability modeling, or service credit frameworks

• Exposure to ML/optimization techniques applied to infrastructure or energy systems

The annual compensation range for this role is listed below.

For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.

Logistics

Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience

Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience

Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position

Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.

Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.

How we're different

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.

The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.

Come work with us!

Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process