Роль четко определена с акцентом на ИИ и Kubernetes, а зарплата выше среднего по рынку, что делает ее привлекательной.
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Высокая зарплатаЧеткие обязанностиПродуктовая компанияФокус на ИИ
Оценка от Hirify AI
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Описание вакансии
Текст:
Hirify AI/Оригинал
TL;DR
Engineering Manager, Scheduler and Fleet Efficiency (Kubernetes/AI): Building and leading infrastructure for Kubernetes scheduling, job launch tooling, and compute-fleet efficiency with an accent on heterogeneous workloads, utilization, queueing, and predictable placement decisions. Focus on setting technical direction for large-scale distributed systems, improving scheduling latency and reliability, and developing a high-performing engineering team.
Location: San Francisco, CA or New York City, NY; hybrid policy requires staff to work from an office at least 25% of the time.
Annual salary: $405,000–$485,000 USD
Company
Anthropic builds reliable, interpretable, and steerable AI systems intended to be safe and beneficial for users and society.
What you will do
Lead and grow the engineering team responsible for the scheduling platform, job-launch tooling, and fleet-efficiency systems.
Set technical direction for scheduling, placement, queueing, and quota management across a large Kubernetes compute fleet.
Partner with capacity planning, research, inference, and product teams to improve workload placement and compute utilization.
Drive the roadmap for scheduler capabilities, fleet utilization, and the developer experience of launching and managing jobs.
Define metrics for utilization, queue wait time, job-start latency, and scheduling quality.
Hire, coach, and develop an inclusive, high-performing engineering team while contributing to engineering-wide initiatives.
Requirements
Experience managing and growing a team of software engineers.
Hands-on software engineering experience as an individual contributor before moving into management.
Experience building or operating large-scale distributed or infrastructure systems in production.
Working knowledge of Kubernetes and cluster scheduling concepts, including resource requests and limits, affinity, priority, preemption, and custom schedulers or controllers.
Excellent written and verbal communication skills.
Bachelor’s degree or equivalent education, training, or experience in a relevant field.
Nice to have
5+ years of engineering management experience leading infrastructure, platform, or compute teams.
Experience owning a cluster scheduler, job orchestration system, or resource manager at scale.
Experience scheduling machine-learning workloads on accelerators and balancing utilization, fairness, and latency.
Experience building developer tooling, observability, or incident-response practices for control-plane systems.
Experience building a culture of belonging and engineering excellence.
Culture & Benefits
Visa sponsorship is available, with immigration-lawyer support, although sponsorship cannot be guaranteed for every role or candidate.
Flexible working hours and a collaborative office environment.
Competitive compensation, optional equity-donation matching, generous vacation, and parental leave.
Highly collaborative work across research, engineering, policy, and business functions.
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