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Capacity Strategy & Operations Lead
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Reach the decision-maker — $5About the role
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 $300M Series E , backed by investors including BOND, IVP, Spark Capital, Greylock, and Conviction. Join us and help build the platform engineers turn to to ship AI products. THE ROLE As a Capacity Strategy & Operations Lead, you will sit at the intersection of supply intelligence, demand forecasting, and cross-functional execution, turning a complex, fast-moving hardware market into a predictable, reliable foundation for our customers and internal engineering teams. This is not a purely analytical role. You will own the end-to-end capacity planning process: from translating customer commitments and growth forecasts into concrete supply requirements, to coordinating fulfillment across vendors, finance, and the infrastructure team, to building the systems that make all of this repeatable and scalable. When supply is constrained and tradeoffs are unavoidable, you are the person in the room who can model the options, make a clear recommendation, and drive alignment fast. You are a strong fit if you have operated at the intersection of strategy and execution before, someone who is equally comfortable building a capacity model in a spreadsheet and running a cross-functional war room when a customer deployment is at risk. EXAMPLE INITIATIVES Demand-Supply Alignment Framework: Build and own the process that translates customer pipeline, signed commitments, and growth projections into a forward-looking GPU demand signal — so the team is never caught flat-footed when a customer scales faster than expected. Constrained Allocation Playbook: Define the decision framework for how Baseten allocates scarce GPU supply across competing customers and regions, including escalation paths and tradeoff criteria for leadership. Capacity War Room Ownership: Lead cross-functional response when a high-stakes capacity situation arises — coordinating across Sales, SRE, Finance, and Vendor relationships to resolve it with minimal customer disruption. Strategic Briefings for Leadership: Produce clear, concise capacity health reports and scenario analyses for senior leadership, enabling confident decisions on customer commitments, vendor negotiations, and CapEx allocation. RESPONSIBILITIES Own the capacity planning process end to end: intake, triage, prioritization, fulfillment tracking, and post-mortem learnings Translate customer commitments, sales pipeline, and infrastructure growth targets into concrete GPU demand forecasts across regions, GPU types, and timelines Partner with Finance to model capacity scenarios, evaluate new supply opportunities, and support CapEx decision-making Work closely with the Capacity Acquisition team to align supply procurement with forward demand, flagging gaps and risks early Coordinate cross-functionally across Sales, SRE, and Infrastructure teams to resolve capacity conflicts and ensure customer commitments are honored Build and maintain the operational cadence that keeps capacity planning structured, visible, and free of ad-hoc Slack chaos Develop reporting and dashboards that give leadership a real-time view of capacity health, utilization trends, and risk exposure Identify recurring operational gaps in the capacity lifecycle and drive process improvements that reduce toil and improve reliability REQUIREMENTS 5+ years of experience in strategy, operations, consulting, finance, or a similarly analytical and execution-oriented role Demonstrated ability to own complex, cross-functional processes with multiple stakeholders and competing priorities Strong quantitative and modeling skills — comfortable building demand forecasts, scenario analyses, and capacity models from scratch Excellent communication skills, with a track record of distilling ambiguous situations into clear recommendations for senior leadership High ownership mindset: you identify what is broken, build the fix, and follow through until it is working Operates well under pressure and in ambiguous, fast-moving environments where the playbook does not yet exist NICE TO HAVE Familiarity with GPU infrastructure, cloud platforms, or AI/ML ecosystem Experience in a high-growth startup or Series B+ environment where operational processes were being built from scratch Exposure to vendor or partner management, particularly in hardware, cloud, or infrastructure contexts 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).
About Baseten
Baseten provides infrastructure for deploying and serving machine learning models in production with fast, scalable inference.
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