Global Capacity Manager

Posted Yesterday
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San Francisco, CA, USA
Hybrid
170K-230K Annually
Senior level
Software
Inference will be the largest market ever created.
The Role
Lead global GPU capacity management across multi-cloud environments, including cluster acquisition, Kubernetes orchestration, workload migration, infrastructure automation, incident response, and GPU fleet maintenance. Build scalable capacity systems, develop Go-based operators, optimize reliability and cost through financial modeling, and coordinate infrastructure initiatives across SRE, Infra, and FDE teams.
Summary Generated by Built In

ABOUT BASETEN

Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products.

THE ROLE
As a Global Capacity Lead at Baseten, you will lead the "engine room" of the company, architecting, securing, and optimizing the global GPU fleet that powers our customers' AI workloads. You’ll own the end-to-end journey of capacity management, from securing multi-million dollar GPU clusters to building the automation that ensures 99.9% uptime across multi-cloud environments.


This role is a great fit for entrepreneurial engineers who want to bridge the gap between high-finance asset management and deep infrastructure engineering. You will act as the fleet orchestrator for the world's most advanced chips, ensuring Baseten never experiences a capacity outage while maintaining elite unit economics.


To be clear, this is a high-stakes engineering role. You will be hands-on with Kubernetes
orchestration while also leading specialized pods focused on the next generation of hardware, like NVIDIA’s Blackwell (B200) architecture.

EXAMPLE INITIATIVES

  • The B200 Frontier: Architecting the infrastructure readiness and deployment strategy
    for Baseten's first Blackwell GPU clusters.
    Global Workload Orchestration: Building "Multi-cloud Capacity Management" systems
    to move customer workloads seamlessly across regions to optimize cost and latency.

  • Precision GPU Triage: Developing automated Go-based operators to identify, cordon,
    and repair unhealthy H100 nodes in under an hour.

The Supply Chain of Intelligence: Partnering with leadership to secure and reserve
dedicated capacity for Baseten’s largest enterprise customers.

RESPONSIBILITIES

  • Lead Specialized Pods: Act as the lead for specific GPU pods (e.g., H100 or B200),
    managing the full lifecycle of acquisition, air traffic control, and maintenance for those
    assets.

  • Advanced Orchestration: Execute complex workload migrations and "sticky"
    deployment drains, ensuring deployment scheduling rules meet strict regional and
    compliance requirements.

  • Build for Scalability: Design and implement the "next version" of Baseten’s capacity
    management system to handle a 10x increase in GPU volume.
    Financial Modeling: Leverage your understanding of unit economics to build ROI
    models for GPU spend, ensuring Baseten scales profitably.

  • Cross-Team Collaboration: Partner with SRE, Infra, and FDE teams to take discrete
    operational tasks off their plate and verify "last mile" follow-through on infrastructure
    changes.

  • Incident Response: Lead capacity-crunch response by rapidly untainting and re-
    coordinating workloads during high-pressure outages.

REQUIREMENTS

  • Bachelor's, Master's, or Ph.D. degree in Computer Science, Engineering, Mathematics,
    or a related field

  • 5+ years of professional work experience in a high-growth environment, preferably at a
    hyperscaler (GCP, AWS, Azure) or a specialized GPU provider

  • Deep expertise in Kubernetes, including hands-on experience with taints, cordons, node
    draining, and custom operators

  • Demonstrated experience with Go or Python in a production-level environment
    Strong financial literacy and the ability to model complex trade-offs between capacity
    reliability and cost

  • High tenacity and collaborative mindset

BENEFITS

  • Competitive compensation, including meaningful equity

  • 100% coverage of medical, dental, and vision insurance for employee and dependents

  • Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!)

  • Paid parental leave

  • Fertility and family-building stipend through Carrot

  • Company-facilitated 401(k)

  • Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities.

Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you.

At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status.

We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).

Skills Required

  • Bachelor's, Master's, or Ph.D. degree in Computer Science, Engineering, Mathematics, or a related field
  • 5+ years of professional work experience in a high-growth environment, preferably at a hyperscaler or specialized GPU provider
  • Deep expertise in Kubernetes, including taints, cordons, node draining, and custom operators
  • Production-level experience with Go or Python
  • Strong financial literacy and ability to model trade-offs between capacity, reliability, and cost
  • High tenacity and collaborative mindset

Baseten Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Baseten and has not been reviewed or approved by Baseten.

  • Fair & Transparent Compensation Feedback suggests pay targets the top of market with explicit ranges in postings and a stated aim to provide 90th percentile salaries with equity. Role descriptions emphasize competitive, experience-based pay bands and meaningful stock grants.
  • Healthcare Strength Healthcare is described as fully covered for medical, dental, and vision for employees and their families, reducing out-of-pocket costs. This comprehensive coverage is consistently highlighted alongside other core benefits.
  • Leave & Time Off Breadth Time off policies include unlimited PTO with a minimum expectation of at least four weeks, 16 paid company holidays, and a company-wide winter break. These elements indicate substantial protected time away from work.

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The Company
HQ: San Francisco, CA
350 Employees
Year Founded: 2019

What We Do

AI’s future won’t be a few massive models built by a handful of labs. It’ll be millions of specialized models embedded into every product, workflow, and experience by the people closest to the customer. The foundation of that future is inference. Inference determines the performance, reliability, latency, and economics of every AI product. For AI to scale globally, it must be as reliable, fast, cost-effective, and high-quality as possible. That’s why Baseten exists. Companies like Abridge, Cursor, Lovable, Notion, and OpenEvidence depend on Baseten to power mission-critical AI workloads in production.

Why Work With Us

We’re an interdisciplinary team of researchers, engineers, and operators building the Inference Cloud our AI future demands. We’re running at a hard systems problem that requires first-principles thinking across the entire stack. The bar is high. We work hard, move fast, and care deeply about quality.

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