Job description

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 compute fleet is one of the largest and most varied in the world, and everything we do from training frontier models to serving Claude depends on getting the right work onto the right hardware at the right time. Our Scheduler team owns that problem. We build the scheduling layer for Anthropic's Kubernetes fleet, the tools researchers and engineers use to launch and manage their jobs, and the systems that make sure the fleet is used as efficiently as possible. When a researcher starts a run, the scheduler decides where it lands and how quickly; when demand outstrips supply, it decides who waits. This team provides the paved path that lets everyone at Anthropic get compute when they need it without becoming an expert in the infrastructure underneath. We're looking for an engineering manager to lead this team. The scheduler is on the critical path for nearly all of Anthropic's compute, and the mandate is expanding quickly: making scheduling work seamlessly across a growing, heterogeneous fleet; raising utilization while keeping jobs starting fast; making the system's decisions predictable and explainable to the people who depend on it; and making the job-launch experience something researchers rarely have to think about. You'll lead a team building infrastructure that the entire research and product organization depends on, and you'll partner closely with capacity planning, research, inference, and product teams to make efficient use of the fleet. Key responsibilities Lead and grow a team of engineers building Anthropic's scheduling platform, job-launch tooling, and fleet-efficiency systems, owning planning, execution, and delivery against key milestones Set technical direction for scheduling, placement, queueing, and quota across Anthropic's compute fleet Partner with capacity planning, research, inference, and product teams to bring workloads onto the paved path and make efficient scheduling decisions Drive the roadmap for scheduler capabilities, fleet utilization, and the developer experience of launching and managing jobs Define and track the metrics that measure fleet efficiency and scheduling quality (utilization, queue wait, job-start latency, etc.) and hold the team accountable to them Create clarity for the team and stakeholders in an ambiguous, fast-moving environment where demand for compute routinely exceeds supply Take an inclusive, equitable approach to hiring, coaching, and career development, and sustain a high-performing, healthy team Represent the team across the engineering organization and contribute to engineering-wide initiatives as a member of Anthropic's engineering management group Minimum qualifications Experience managing and growing a team of software engineers A hands-on software engineering background as an individual contributor prior to moving into management Experience building or operating large-scale distributed or infrastructure systems in production Working knowledge of Kubernetes and cluster scheduling concepts, such as resource requests and limits, affinity, priority and preemption, and custom schedulers or controllers Excellent written and verbal communication skills, including the ability to create clarity across teams Preferred qualifications 5+ years of engineering management experience, including leading infrastructure, platform, or compute teams Experience owning a cluster scheduler, job orchestration system, or resource manager at scale Familiarity with scheduling ML workloads on accelerators and the tradeoffs between utilization, fairness, and latency Experience building developer tooling that other engineers rely on every day A background in observability or incident response for control-plane systems, and a track record of improving production reliability A track record of building a culture of belonging and of engineering excellence Low ego, high empathy, and a habit of leading by example 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: $405,000 — $485,000 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 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.

Requirements

Must-haves

Lead and grow a team of engineers building Anthropic's scheduling platform, job-launch tooling, and fleet-efficiency systems, owning planning, execution, and delivery against key milestones
Set technical direction for scheduling, placement, queueing, and quota across Anthropic's compute fleet
Partner with capacity planning, research, inference, and product teams to bring workloads onto the paved path and make efficient scheduling decisions
Drive the roadmap for scheduler capabilities, fleet utilization, and the developer experience of launching and managing jobs
Define and track the metrics that measure fleet efficiency and scheduling quality (utilization, queue wait, job-start latency, etc.) and hold the team accountable to them
Create clarity for the team and stakeholders in an ambiguous, fast-moving environment where demand for compute routinely exceeds supply
Take an inclusive, equitable approach to hiring, coaching, and career development, and sustain a high-performing, healthy team
Represent the team across the engineering organization and contribute to engineering-wide initiatives as a member of Anthropic's engineering management group
Experience managing and growing a team of software engineers
A hands-on software engineering background as an individual contributor prior to moving into management
Experience building or operating large-scale distributed or infrastructure systems in production
Working knowledge of Kubernetes and cluster scheduling concepts, such as resource requests and limits, affinity, priority and preemption, and custom schedulers or controllers
Excellent written and verbal communication skills, including the ability to create clarity across teams
5+ years of engineering management experience, including leading infrastructure, platform, or compute teams

Nice-to-haves

Experience owning a cluster scheduler, job orchestration system, or resource manager at scale
Familiarity with scheduling ML workloads on accelerators and the tradeoffs between utilization, fairness, and latency
Experience building developer tooling that other engineers rely on every day
A background in observability or incident response for control-plane systems, and a track record of improving production reliability
A track record of building a culture of belonging and of engineering excellence
Low ego, high empathy, and a habit of leading by example
The annual compensation range for this role is listed below.
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.
How we're different
Come work with us!

Application prep

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Keywords to mirror

aikubernetesml

Platform: greenhouse
Effort: quick

Benefits

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Parental Leave