Data Center Electrical Engineer

About the role

Training and serving frontier AI models requires compute infrastructure at a scale and density that pushes past what conventional data center designs were built to handle. Anthropic's Data Center team is responsible for delivering that physical infrastructure — partnering with build partners, equipment manufacturers, and utilities to stand up facilities that can reliably power some of the largest accelerator clusters in the industry.

As a Data Center Electrical Engineer, you'll own the electrical design of our facilities from the building service entrance through to the rack. You'll develop and maintain the reference designs and specifications our build partners work against, review their engineering submittals, and run the analysis needed to make confident decisions on topology, redundancy, and equipment selection. You'll ensure the electrical architecture keeps pace with rapidly increasing rack densities and the unique load characteristics of large-scale ML training.

This is a highly cross-functional role. You'll work closely with our hardware and compute teams to translate accelerator requirements into electrical design criteria, and with supply chain to qualify equipment vendors and create optionality in a constrained market. Strong candidates will bring deep mission-critical electrical design experience and the judgment to make sound trade-offs when the standard playbook doesn't apply.

Responsibilities

You may be a good fit if you

Strong candidates may also have

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.

Annual Salary:

$320,000—$405,000 USD

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 w

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