{"version":"0.1","company":{"name":"YubHub","url":"https://yubhub.co","jobsUrl":"https://yubhub.co/jobs/skill/error-propagation"},"x-facet":{"type":"skill","slug":"error-propagation","display":"Error Propagation","count":3},"x-feed-size-limit":100,"x-feed-sort":"enriched_at desc","x-feed-notice":"This feed contains at most 100 jobs (the most recently enriched). For the full corpus, use the paginated /stats/by-facet endpoint or /search.","x-generator":"yubhub-xml-generator","x-rights":"Free to redistribute with attribution: \"Data by YubHub (https://yubhub.co)\"","x-schema":"Each entry in `jobs` follows https://schema.org/JobPosting. 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You&#39;ll work closely with internal teams to understand their needs, burn down errors and edge cases, and build a roadmap that anticipates where the product needs to go. This is a role for someone who finds satisfaction in both the craft of building reliable systems and the empathy required to serve developers and researchers well.</p>\n<p><strong>Responsibilities</strong></p>\n<ul>\n<li>Contribute to the client library, API surface, and underlying infrastructure for Anthropic&#39;s sandboxing system, ensuring it is reliable, well-documented, and intuitive to use</li>\n<li>Drive down error rates and improve correctness through systematic debugging, monitoring, and proactive fixes</li>\n<li>Help develop and maintain a product roadmap for sandboxing capabilities, balancing immediate needs with long-term architectural improvements</li>\n<li>Partner closely with internal teams using the sandboxing system to understand their requirements, debug issues, and build tooling that serves their use cases</li>\n<li>Respond to incidents and production issues with urgency, conducting thorough root cause analysis and implementing preventive measures</li>\n<li>Build comprehensive testing, observability, and documentation to ensure the system meets a high quality bar</li>\n<li>Collaborate across the sandboxing team, flexing between client-side and infrastructure work as needed</li>\n</ul>\n<p><strong>You May Be a Good Fit If You</strong></p>\n<ul>\n<li>Have 5+ years of software engineering experience, with meaningful time spent maintaining libraries, SDKs, or developer-facing APIs</li>\n<li>Obsess over developer experience,you&#39;ve thought deeply about API design, error propagation, documentation, and the small details that make a library feel well-crafted</li>\n<li>Have experience operating complex distributed systems</li>\n<li>Bring a track record of systematically improving reliability,you&#39;ve burned down error budgets, built monitoring, and driven issues to resolution</li>\n<li>Can develop and articulate a long-term vision for a product, translating user feedback and technical constraints into a coherent roadmap</li>\n<li>Are comfortable with ambiguity and can context-switch between reactive incident work and proactive product development</li>\n<li>Communicate clearly with both technical and non-technical stakeholders</li>\n</ul>\n<p><strong>Strong Candidates May Also Have</strong></p>\n<ul>\n<li>Experience as a founder or early engineer at an infrastructure-focused startup, where you owned a product end-to-end</li>\n<li>Background in security, sandboxing, or isolation technologies (containers, VMs, seccomp, namespaces, etc.)</li>\n<li>Open-source contributions in the Python ecosystem</li>\n<li>Experience building developer tools, CLIs, or platforms used by other engineers</li>\n<li>History of working on incident response and on-call rotations for production systems</li>\n<li>Exposure to reinforcement learning or model training infrastructure</li>\n</ul>\n<p><strong>Representative Projects</strong></p>\n<p>These are examples of past work that would indicate a good fit,not a description of the role itself:</p>\n<ul>\n<li>Maintaining an open source SDK through multiple major version upgrades while minimizing breaking changes for users</li>\n<li>Leading an initiative to reduce P0 incidents by XX% through improved error handling, retries, and observability</li>\n<li>Building a developer platform at a startup from zero to product-market fit, iterating based on user feedback</li>\n<li>Embedding with an internal team for a quarter to deeply understand their workflows and shipping targeted improvements to a piece of infrastructure they rely on</li>\n<li>Developing a multi-quarter roadmap for a developer tools product, balancing user requests with technical debt reduction</li>\n</ul>\n<p><strong>Logistics</strong></p>\n<ul>\n<li>Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience</li>\n<li>Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience</li>\n<li>Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position</li>\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<li>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.</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_272bd1ad-99d","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://www.anthropic.com/","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/5083039008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$300,000-$405,000 USD","x-skills-required":["software engineering","infrastructure expertise","developer experience","API design","error propagation","documentation","distributed systems","complex systems","reliability","monitoring","root cause analysis","preventive measures","testing","observability","collaboration","communication"],"x-skills-preferred":["founder","early engineer","security","sandboxing","isolation technologies","open-source contributions","developer tools","incident response","on-call rotations","reinforcement learning","model training infrastructure"],"datePosted":"2026-04-18T15:51:53.000Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA | New York City, NY"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"software engineering, infrastructure expertise, developer experience, API design, error propagation, documentation, distributed systems, complex systems, reliability, monitoring, root cause analysis, preventive measures, testing, observability, collaboration, communication, founder, early engineer, security, sandboxing, isolation technologies, open-source contributions, developer tools, incident response, on-call rotations, reinforcement learning, model training infrastructure","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":300000,"maxValue":405000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_faffae87-882"},"title":"Staff Software Engineer - GenAI Performance and Kernel","description":"<p>As a staff software engineer for GenAI Performance and Kernel, you will own the design, implementation, optimization, and correctness of the high-performance GPU kernels powering our GenAI inference stack. You will lead development of highly-tuned, low-level compute paths, manage trade-offs between hardware efficiency and generality, and mentor others in kernel-level performance engineering.</p>\n<p>Key responsibilities include:</p>\n<ul>\n<li>Leading the design, implementation, benchmarking, and maintenance of core compute kernels optimized for various hardware backends (GPU, accelerators)</li>\n<li>Driving the performance roadmap for kernel-level improvements: vectorization, tensorization, tiling, fusion, mixed precision, sparsity, quantization, memory reuse, scheduling, auto-tuning, etc.</li>\n<li>Integrating kernel optimizations with higher-level ML systems</li>\n<li>Building and maintaining profiling, instrumentation, and verification tooling to detect correctness, performance regressions, numerical issues, and hardware utilization gaps</li>\n<li>Leading performance investigations and root-cause analysis on inference bottlenecks, e.g. memory bandwidth, cache contention, kernel launch overhead, tensor fragmentation</li>\n<li>Establishing coding patterns, abstractions, and frameworks to modularize kernels for reuse, cross-backend portability, and maintainability</li>\n<li>Influencing system architecture decisions to make kernel improvements more effective (e.g. memory layout, dataflow scheduling, kernel fusion boundaries)</li>\n<li>Mentoring and guiding other engineers working on lower-level performance, providing code reviews, and helping set best practices</li>\n<li>Collaborating with infrastructure, tooling, and ML teams to roll out kernel-level optimizations into production, and monitoring their impact</li>\n</ul>\n<p>Requirements include:</p>\n<ul>\n<li>BS/MS/PhD in Computer Science, or a related field</li>\n<li>Deep hands-on experience writing and tuning compute kernels (CUDA, Triton, OpenCL, LLVM IR, assembly or similar sort) for ML workloads</li>\n<li>Strong knowledge of GPU/accelerator architecture: warp structure, memory hierarchy (global, shared, register, L1/L2 caches), tensor cores, scheduling, SM occupancy, etc.</li>\n<li>Experience with advanced optimization techniques: tiling, blocking, software pipelining, vectorization, fusion, loop transformations, auto-tuning</li>\n<li>Familiarity with ML-specific kernel libraries (cuBLAS, cuDNN, CUTLASS, oneDNN, etc.) or open kernels</li>\n<li>Strong debugging and profiling skills (Nsight, NVProf, perf, vtune, custom instrumentation)</li>\n<li>Experience reasoning about numerical stability, mixed precision, quantization, and error propagation</li>\n<li>Experience in integrating optimized kernels into real-world ML inference systems; 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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.</p>\n<p><strong>About the Role</strong></p>\n<p>Anthropic&#39;s sandboxing infrastructure enables Claude to safely execute code and interact with external systems. As we expand Claude&#39;s capabilities, the reliability, security, and developer experience of this infrastructure becomes increasingly critical. We&#39;re looking for an engineer to join the sandboxing team and help shape both the client-side library/API and the underlying infrastructure.</p>\n<p>In this role, you&#39;ll combine deep infrastructure expertise with an obsession for developer experience. You&#39;ll help maintain and evolve a system that must be correct, performant, and intuitive to use. You&#39;ll work closely with internal teams to understand their needs, burn down errors and edge cases, and build a roadmap that anticipates where the product needs to go. This is a role for someone who finds satisfaction in both the craft of building reliable systems and the empathy required to serve developers and researchers well.</p>\n<p><strong>Responsibilities</strong></p>\n<ul>\n<li>Contribute to the client library, API surface, and underlying infrastructure for Anthropic&#39;s sandboxing system, ensuring it is reliable, well-documented, and intuitive to use</li>\n</ul>\n<ul>\n<li>Drive down error rates and improve correctness through systematic debugging, monitoring, and proactive fixes</li>\n</ul>\n<ul>\n<li>Help develop and maintain a product roadmap for sandboxing capabilities, balancing immediate needs with long-term architectural improvements</li>\n</ul>\n<ul>\n<li>Partner closely with internal teams using the sandboxing system to understand their requirements, debug issues, and build tooling that serves their use cases</li>\n</ul>\n<ul>\n<li>Respond to incidents and production issues with urgency, conducting thorough root cause analysis and implementing preventive measures</li>\n</ul>\n<ul>\n<li>Build comprehensive testing, observability, and documentation to ensure the system meets a high quality bar</li>\n</ul>\n<ul>\n<li>Collaborate across the sandboxing team, flexing between client-side and infrastructure work as needed</li>\n</ul>\n<p><strong>You May Be a Good Fit If You</strong></p>\n<ul>\n<li>Have 5+ years of software engineering experience, with meaningful time spent maintaining libraries, SDKs, or developer-facing APIs</li>\n</ul>\n<ul>\n<li>Obsess over developer experience—you&#39;ve thought deeply about API design, error propagation, documentation, and the small details that make a library feel well-crafted</li>\n</ul>\n<ul>\n<li>Have experience operating complex distributed systems</li>\n</ul>\n<ul>\n<li>Bring a track record of systematically improving reliability—you&#39;ve burned down error budgets, built monitoring, and driven issues to resolution</li>\n</ul>\n<ul>\n<li>Can develop and articulate a long-term vision for a product, translating user feedback and technical constraints into a coherent roadmap</li>\n</ul>\n<ul>\n<li>Are comfortable with ambiguity and can context-switch between reactive incident work and proactive product development</li>\n</ul>\n<ul>\n<li>Communicate clearly with both technical and non-technical stakeholders</li>\n</ul>\n<p><strong>Strong Candidates May Also Have</strong></p>\n<ul>\n<li>Experience as a founder or early engineer at an infrastructure-focused startup, where you owned a product end-to-end</li>\n</ul>\n<ul>\n<li>Background in security, sandboxing, or isolation technologies (containers, VMs, seccomp, namespaces, etc.)</li>\n</ul>\n<ul>\n<li>Open-source contributions in the Python ecosystem</li>\n</ul>\n<ul>\n<li>Experience building developer tools, CLIs, or platforms used by other engineers</li>\n</ul>\n<ul>\n<li>History of working on incident response and on-call rotations for production systems</li>\n</ul>\n<ul>\n<li>Exposure to reinforcement learning or model training infrastructure</li>\n</ul>\n<p><strong>Representative Projects</strong></p>\n<p>These are examples of past work that would indicate a good fit—not a description of the role itself:</p>\n<ul>\n<li>Maintaining an open source SDK through multiple major version upgrades while minimizing breaking changes for users</li>\n</ul>\n<ul>\n<li>Leading an initiative to reduce P0 incidents by XX% through improved error handling, retries, and observability</li>\n</ul>\n<ul>\n<li>Building a developer platform at a startup from zero to product-market fit, iterating based on user feedback</li>\n</ul>\n<ul>\n<li>Embedding with an internal team for a quarter to deeply understand their workflows and shipping targeted improvements to a piece of infrastructure they rely on</li>\n</ul>\n<ul>\n<li>Developing a multi-quarter roadmap for a developer tools product, balancing user requests with technical debt reduction</li>\n</ul>\n<p><strong>Logistics</strong></p>\n<p><strong>Education requirements:</strong> We require at least a Bachelor&#39;s degree in a related field or equivalent experience. <strong>Location-based hybrid policy:</strong> 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.</p>\n<p><strong>Visa sponsorship:</strong> 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><strong>We encourage you to apply even if you do not believe you meet every single qualification.</strong> 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. We think AI systems like the ones we&#39;re building can have a huge impact on society, and we want to make sure that the people building them are representative of the people they&#39;ll be serving.</p>\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_4396bfcf-940","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://job-boards.greenhouse.io","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/5083039008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$300,000 - $405,000USD","x-skills-required":["software engineering","API design","error propagation","documentation","complex distributed systems","reliability","observability","testing","security","sandboxing","isolation technologies","containers","VMs","seccomp","namespaces","Python ecosystem","developer tools","CLIs","platforms","incident response","on-call rotations","reinforcement learning","model training infrastructure"],"x-skills-preferred":["founder","early engineer","infrastructure-focused startup","open-source contributions","developer platform","product-market fit","user feedback","incident response","on-call rotations","reinforcement learning","model training infrastructure"],"datePosted":"2026-03-08T14:03:30.986Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA | New York City, NY"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"software engineering, API design, error propagation, documentation, complex distributed systems, reliability, observability, testing, security, sandboxing, isolation technologies, containers, VMs, seccomp, namespaces, Python ecosystem, developer tools, CLIs, platforms, incident response, on-call rotations, reinforcement learning, model training infrastructure, founder, early engineer, infrastructure-focused startup, open-source contributions, developer platform, product-market fit, user feedback, incident response, on-call rotations, reinforcement learning, model training infrastructure","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":300000,"maxValue":405000,"unitText":"YEAR"}}}]}