[P] Compute Efficiency Engineer

About Anthropic

Anthropics 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.

At Anthropic we are building some of the most complex and large-scale AI infrastructure in the world. As that infrastructure scales rapidly so does the imperative to optimize how we use it. As an Infrastructure Optimization & Efficiency Engineer on the Capacity team you will play a central role in making our systems more performant cost-effective and sustainablewithout compromising reliability or latency.

You will work across the full infrastructure stack from cloud platforms and networking to application-level performance and will bridge the gap between high-level research needs and low-level hardware constraints to build the most efficient AI infrastructure in the world. You will help with building the telemetry cost attribution and optimization frameworks that ensure every dollar of our infrastructure investment delivers maximum value. This is a high-impact cross-functional role at the intersection of systems engineering financial optimization and AI infrastructure.

Responsibilities:

• Build and evolve telemetry and monitoring systems to provide deep visibility into infrastructure performance utilization and costs across our cloud and datacenter fleets.

• Design and implement cost attribution frameworks for our multi-tenant infrastructure enabling teams to understand and optimize their resource consumption.

• Identify and resolve performance bottlenecks and capacity hotspots through deep analysis of distributed systems at scale.

• Partner closely with cloud service providers and internal stakeholders to optimize cluster configurations workload placement and resource utilization across AI training and inference workloadsincluding large-scale clusters spanning thousands to hundreds of thousands of machines.

• Develop and champion engineering practices around efficiency driving a culture of performance awareness and cost-conscious design across Anthropic.

• Collaborate with research and product teams to deeply understand their infrastructure needs and design solutions that balance performance with cost efficiency.

• Drive architectural improvements and code-level optimizations across multiple services and platforms to deliver measurable utilization and performance gains.

You may be a good fit if you:

• Have 6 years of relevant industry experience 1 year leading large scale complex projects or teams as an engineer or tech lead

• Deep expertise in distributed systems at scale with a strong focus on infrastructure reliability scalability and continuous improvement.

• Strong proficiency in at least one programming language (e.g. Python Rust Go Java)

• Hands-on experience with cloud infrastructure including Kubernetes Infrastructure as Code and major cloud providers such as AWS or GCP.

• Experience optimizing end-to-end performance of distributed systems including workload right-sizing and resource utilization tuning.

• You possess a deep curiosity for how things work under the hood and have a proven ability to work independently to solve opaque performance issues

• Experience designing or working with performance and utilization monitoring tools in large-scale distributed environments.

• Strong problem-solving skills with the ability to work independently and navigate ambiguity.

• Excellent communication and collaboration skillsyou will work closely with internal and external stakeholders to build consensus and drive projects forward.

Strong candidates may have:

• Experience with machine learning infrastructure workloads as well as associated networking technologies like NCCL.

• Low level systems experience for example linux kernel tuning and eBPF

• Quickly understanding systems design tradeoffs keeping track of rapidly evolving software systems

• Published work in performance optimization and scaling distributed systems

Logistics

Education requirements: We require at least a Bachelors degree in a related field or equivalent experience.

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 arent 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 youre interested in this work. We think AI systems like the ones were 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 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 youre ever unsure about a communication dont click any linksvisit for confirmed position openings.

How were 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. Were 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 aboutour policyfor using AI in our application process