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YubHub-native raw fields carry `x-` prefix.","jobs":[{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_9a0bf3cb-901"},"title":"Performance Modeling Lead","description":"<p>We are seeking a Performance Modeling Lead to build and lead a small, high-impact team responsible for answering forward-looking architectural questions across AI infrastructure systems.</p>\n<p>You will develop modeling frameworks and methodologies to evaluate system-level tradeoffs and guide key design decisions. Your work will directly influence reference architectures, vendor designs, and long-term infrastructure strategy.</p>\n<p>This role sits at the intersection of AI workloads, system architecture, and quantitative modeling, and requires strong technical judgment, ownership, and the ability to translate complex analysis into clear, actionable guidance.</p>\n<p>Key Responsibilities:</p>\n<ul>\n<li>Build and own a performance modeling framework/toolchain to evaluate AI systems across multiple levels of abstraction.</li>\n<li>Analyze and quantify architectural tradeoffs across compute, memory, networking, storage, and system topology.</li>\n<li>Develop performance models to guide decisions on:</li>\n<li>scale-up vs. scale-out architectures</li>\n<li>interconnect and network design</li>\n<li>memory hierarchy and system balance.</li>\n<li>Translate modeling outputs into clear recommendations for internal teams and external hardware vendors.</li>\n<li>Influence reference designs and vendor roadmaps through data-driven insights.</li>\n<li>Partner closely with machine learning, systems, and hardware teams to understand workload characteristics and requirements.</li>\n<li>Lead and grow a small team (2–3 engineers), setting technical direction and maintaining high standards for modeling rigor.</li>\n<li>Continuously improve modeling fidelity by validating against real system behavior and measurements.</li>\n</ul>\n<p>Qualifications:</p>\n<ul>\n<li>Have experience owning or building performance modeling frameworks used to drive real system design decisions.</li>\n<li>Have deep knowledge of AI/ML workloads, including training and/or inference at scale.</li>\n<li>Understand system-level tradeoffs across compute, memory, and networking in large-scale distributed systems.</li>\n<li>Are comfortable working across abstraction layers,from workload behavior to hardware implementation.</li>\n<li>Have experience using modeling (analytical or simulation) to inform architectural decisions.</li>\n<li>Can operate in ambiguous problem spaces and turn open-ended questions into structured analysis.</li>\n<li>Communicate clearly and influence both internal teams and external partners.</li>\n</ul>\n<p>Preferred Skills:</p>\n<ul>\n<li>Experience working with hardware vendors (ODM/JDM, silicon, networking).</li>\n<li>Background in data center infrastructure or hyperscale systems.</li>\n<li>Familiarity with accelerators (GPUs/ASICs) and interconnects (e.g., NVLink, InfiniBand, Ethernet).</li>\n<li>Experience influencing hardware roadmaps or reference architectures.</li>\n<li>Prior experience leading or mentoring engineers.</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_9a0bf3cb-901","directApply":true,"hiringOrganization":{"@type":"Organization","name":"OpenAI","sameAs":"https://openai.com/","logo":"https://logos.yubhub.co/openai.com.png"},"x-apply-url":"https://jobs.ashbyhq.com/openai/f2293c9f-d036-4198-a268-3dad738c8d19","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"Full time","x-salary-range":"$342K – $555K","x-skills-required":["performance modeling","system architecture","quantitative modeling","AI workloads","machine learning","systems engineering","hardware engineering"],"x-skills-preferred":["hardware vendors","data center infrastructure","hyperscale systems","accelerators","interconnects","hardware roadmaps","reference architectures"],"datePosted":"2026-04-24T12:21:47.132Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco; Seattle"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"performance modeling, system architecture, quantitative modeling, AI workloads, machine learning, systems engineering, hardware engineering, hardware vendors, data center infrastructure, hyperscale systems, accelerators, interconnects, hardware roadmaps, reference architectures","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":342000,"maxValue":555000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_459e7356-55d"},"title":"3P Architect","description":"<p>We are seeking a 3P Architect to define and drive rack- and cluster-level reference designs in collaboration with external partners. This role is responsible for translating workload requirements and system-level goals into concrete architectures, aligning partners on critical design attributes, and ensuring vendor roadmaps meet our infrastructure needs.</p>\n<p>You will work closely with performance modeling and internal architecture teams to evaluate tradeoffs, while owning the end-to-end definition and execution of third-party system designs. This includes identifying gaps in current technologies, driving vendor development, and shaping future infrastructure capabilities.</p>\n<p>This role requires strong system intuition, cross-functional leadership, and the ability to operate effectively across internal teams and external ecosystems.</p>\n<p>Key Responsibilities:</p>\n<ul>\n<li>Define rack- and cluster-level reference architectures for AI infrastructure deployments.</li>\n<li>Translate workload requirements into clear system design specifications and partner deliverables.</li>\n<li>Collaborate with performance modeling teams to evaluate architectural tradeoffs and system behaviors.</li>\n<li>Align internal stakeholders and external partners on critical system attributes (performance, cost, power, reliability, scalability).</li>\n<li>Identify gaps in current technology offerings and drive vendors (ODM/JDM, silicon, networking) to close those gaps.</li>\n<li>Influence and shape vendor roadmaps to meet future infrastructure needs.</li>\n<li>Track emerging technologies and evaluate their applicability to AI systems.</li>\n<li>Define and lead proof-of-concept (PoC) efforts to validate new architectures and technologies.</li>\n<li>Act as a key interface between OpenAI and external partners, ensuring execution against design intent.</li>\n</ul>\n<p>Qualifications:</p>\n<ul>\n<li>Have strong experience in system architecture for large-scale infrastructure or data center environments.</li>\n<li>Understand AI workload characteristics and how they map to system-level design decisions.</li>\n<li>Are comfortable working with performance modeling outputs to inform architectural direction.</li>\n<li>Have experience working with or managing hardware vendors (ODM/JDM, silicon, networking).</li>\n<li>Can drive alignment across multiple stakeholders with competing constraints.</li>\n<li>Have a track record of turning ambiguous requirements into clear, executable system designs.</li>\n<li>Are proactive in identifying gaps and driving solutions across organizational boundaries.</li>\n</ul>\n<p>Preferred Skills:</p>\n<ul>\n<li>Experience defining rack- or cluster-level systems for hyperscale or AI workloads.</li>\n<li>Familiarity with accelerators (GPUs/ASICs), interconnects, and data center networking architectures.</li>\n<li>Experience influencing vendor roadmaps and reference designs.</li>\n<li>Background in infrastructure deployment, hardware engineering, or systems integration.</li>\n<li>Experience leading PoCs or early-stage hardware validation efforts.</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_459e7356-55d","directApply":true,"hiringOrganization":{"@type":"Organization","name":"OpenAI","sameAs":"https://openai.com","logo":"https://logos.yubhub.co/openai.com.png"},"x-apply-url":"https://jobs.ashbyhq.com/openai/e2afdede-a222-4825-b2fc-fec439a7c893","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"Full time","x-salary-range":"$342K – $555K","x-skills-required":["system architecture","large-scale infrastructure","data center environments","AI workload characteristics","performance modeling","hardware vendors","cross-functional leadership"],"x-skills-preferred":["hyperscale or AI workloads","accelerators","interconnects","data center networking architectures","vendor roadmaps","reference designs","infrastructure deployment","hardware engineering","systems integration"],"datePosted":"2026-04-24T12:21:42.510Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco; Seattle"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"system architecture, large-scale infrastructure, data center environments, AI workload characteristics, performance modeling, hardware vendors, cross-functional leadership, hyperscale or AI workloads, accelerators, interconnects, data center networking architectures, vendor roadmaps, reference designs, infrastructure deployment, hardware engineering, systems integration","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":342000,"maxValue":555000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_a88f73e0-fbc"},"title":"Systems Engineer (Network / Storage / Systems)","description":"<p>We are seeking a System Engineer (Network / Storage / Systems) to help architect, validate, and operationalize the core infrastructure systems that enable Stargate deployments.</p>\n<p>In this role, you will work across networking, storage, system bring-up, hardware debugging, and cluster readiness. You will partner closely with hardware engineering, cluster software, infrastructure operations, and external vendors to ensure new systems are deployed efficiently and run reliably at scale.</p>\n<p>This role is ideal for engineers who can operate across hardware and software boundaries, solve ambiguous technical problems, and drive complex systems into production.</p>\n<p>Key Responsibilities:</p>\n<ul>\n<li>Own system engineering workstreams across one or more critical domains including networking, storage, system validation, or bring-up.</li>\n<li>Design and improve top-of-network architectures spanning frontend, WAN, OOB, firewall, and adjacent infrastructure layers.</li>\n<li>Drive logical network readiness including routing, configuration management, provisioning, and issue resolution.</li>\n<li>Define storage architectures across in-rack, in-pod, cluster, and cloud tiers with focus on performance, lifecycle, and cost efficiency.</li>\n<li>Evaluate vendor hardware and infrastructure proposals, providing technical feedback on architecture, reliability, and operational fit.</li>\n<li>Lead system bring-up for new hardware platforms including imaging, provisioning, validation, and readiness for production deployment.</li>\n<li>Debug complex system faults across firmware, NIC, GPU, server, and platform layers; 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Infrastructure team member to drive the planning and execution of programs critical to Anthropic&#39;s compute infrastructure strategy.</p>\n<p>In this role, you will manage internal and external stakeholders to bring clarity to our compute technology roadmaps, help prioritise across technical and non-technical teams, and focus on securing and delivering compute capacity.</p>\n<p>Anthropic&#39;s AI models are available on both our first-party platforms (claude.ai and our API) as well as through our major cloud partners. Ensuring tight coordination between our internal teams and external partners is essential to our ability to stay on the frontier of AI development.</p>\n<p>You will work closely with engineering, finance, and partnership teams to drive execution of technical roadmaps, support deal structuring, and manage the operational aspects of our compute partnerships.</p>\n<p>This role combines technical program management with elements of strategic operations, partnership development, and financial analysis. You will be an integral part of a team focused on securing the compute resources Anthropic needs to pursue its mission of developing safe, beneficial AI systems.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Drive cross-functional coordination across Engineering, Finance, and external partners to define, scope, and deliver on compute partnership initiatives</li>\n</ul>\n<ul>\n<li>Develop and maintain detailed project plans, timelines, and status reporting for technical programs related to compute infrastructure and partnerships</li>\n</ul>\n<ul>\n<li>Partner with engineering leaders to translate technical requirements into actionable roadmaps and track execution against milestones</li>\n</ul>\n<ul>\n<li>Support the structuring and negotiation of strategic compute deals, including financial modeling, term analysis, and vendor evaluation</li>\n</ul>\n<ul>\n<li>Build and maintain relationships with key stakeholders at cloud providers and infrastructure partners</li>\n</ul>\n<ul>\n<li>Develop and manage systems, processes, and documentation to support program management efficiency and stakeholder visibility</li>\n</ul>\n<ul>\n<li>Analyze financial and operational data to inform decision-making on compute capacity planning and vendor strategy</li>\n</ul>\n<ul>\n<li>Provide clear and transparent reporting on program status, issues, and risks to leadership</li>\n</ul>\n<p>You might be a good fit if you have:</p>\n<ul>\n<li>8-10 years of experience in technical product/program management, business development, or strategic partnerships roles at technology companies</li>\n</ul>\n<ul>\n<li>Experience structuring and negotiating strategic customer deals or partnerships within the technology space (cloud services, semiconductors, data center/infrastructure)</li>\n</ul>\n<ul>\n<li>Background in cloud computing, data center infrastructure, compute/silicon development, or technology-focused investment banking or consulting</li>\n</ul>\n<ul>\n<li>Familiarity with data center infrastructure, compute hardware, and/or silicon development cycles</li>\n</ul>\n<ul>\n<li>Comfort with financial analysis and modeling; experience with vendor financing arrangements is a plus</li>\n</ul>\n<ul>\n<li>Strong interpersonal and communication skills with the ability to influence and align diverse stakeholders</li>\n</ul>\n<ul>\n<li>Ability to drive clarity in ambiguous environments and manage competing priorities with high-quality execution</li>\n</ul>\n<ul>\n<li>A track record of managing cross-functional initiatives in fast-paced, scaling technology environments</li>\n</ul>\n<ul>\n<li>A passion for Anthropic&#39;s mission and ensuring safe AI development</li>\n</ul>\n<p>Strong candidates may also have:</p>\n<ul>\n<li>Experience managing external partnerships with large-scale cloud providers or hardware vendors</li>\n</ul>\n<ul>\n<li>Understanding of AI/ML infrastructure requirements and compute capacity planning</li>\n</ul>\n<ul>\n<li>Experience with vendor financing, equipment leasing, or infrastructure investment analysis</li>\n</ul>\n<ul>\n<li>Background in technical due diligence or technology M&amp;A</li>\n</ul>\n<p>The annual compensation range for this role is $250,000-$310,000 USD.</p>\n<p>Logistics:</p>\n<ul>\n<li>Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience</li>\n</ul>\n<ul>\n<li>Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience</li>\n</ul>\n<ul>\n<li>Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position</li>\n</ul>\n<ul>\n<li>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.</li>\n</ul>\n<p>Visa sponsorship: We do sponsor visas! However, we aren&#39;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.</p>\n<p>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&#39;re interested in this work.</p>\n<p>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&#39;re ever unsure about a communication, don&#39;t click any links,visit anthropic.com/careers directly for confirmed position openings.</p>\n<p>How we&#39;re different:</p>\n<p>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&#39;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.</p>\n<p>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 &amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.</p>\n<p>Come work with us!</p>\n<p>Anthropic is a public benefit corporation headquartered in San Francisco. 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