{"version":"0.1","company":{"name":"YubHub","url":"https://yubhub.co","jobsUrl":"https://yubhub.co/jobs/skill/ml-infra"},"x-facet":{"type":"skill","slug":"ml-infra","display":"Ml Infra","count":46},"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. YubHub-native raw fields carry `x-` prefix.","jobs":[{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_b40b693d-a0d"},"title":"Senior Software Engineer, Agentic Data Products","description":"<p>We&#39;re forming a new Agentic Data Products team focused on building the next generation of agent-powered tools that ground AI in real operational workflows. Our goal is to help enterprises demystify their data layers and deploy intelligent, agentic systems that can reason over data, take action, and deliver measurable outcomes.</p>\n<p>This is a 0→1 build team. We’re looking for a sharp, product-minded Senior Engineer who thrives in ambiguity, moves quickly, and enjoys building new systems from scratch alongside customers and cross-functional partners. You’ll work closely with product, forward-deployed engineers, data scientists, and applied AI teams to turn real-world problems into scalable, production solutions.</p>\n<p>If you like shipping fast, owning outcomes, and working across the stack,from polished frontends to distributed backends to LLM integrations,this role is for you.</p>\n<p><strong>Responsibilities</strong></p>\n<ul>\n<li>Own major full-stack product areas, driving features from concept and design through production deployment</li>\n<li>Build intuitive, high-performance frontend experiences using React + TypeScript</li>\n<li>Develop reliable backend services in Python, working with distributed systems, data pipelines, and AI/ML infrastructure</li>\n<li>Integrate LLMs, vector databases, and agentic frameworks to power intelligent workflows and decision-making systems</li>\n<li>Ship quickly through tight experimentation loops while maintaining high quality and reliability</li>\n<li>Help define the technical direction and architecture of a brand-new team and product surface</li>\n<li>Adapt across the stack and learn new tools as needed to solve real problems end-to-end</li>\n</ul>\n<p><strong>Ideal Experience</strong></p>\n<ul>\n<li>5+ years of full-time software engineering experience</li>\n<li>0-1 product build experience</li>\n<li>Familiarity with LLMs, embeddings, vector databases, or modern AI data products/tools</li>\n<li>Experience with distributed systems and cloud-based architectures</li>\n<li>Prior experience mentoring or leading team</li>\n</ul>\n<p><strong>What We Value</strong></p>\n<ul>\n<li>Strong product intuition and customer empathy</li>\n<li>Bias toward action and rapid iteration</li>\n<li>Ownership mentality , you see problems through to outcomes</li>\n<li>Comfort collaborating across engineering, product, data science, and applied AI</li>\n<li>Excitement about building agentic systems that make AI genuinely useful in the real world</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_b40b693d-a0d","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Scale","sameAs":"https://scale.com/","logo":"https://logos.yubhub.co/scale.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/scaleai/jobs/4653827005","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$216,000-$270,000 USD","x-skills-required":["React","TypeScript","Python","Distributed systems","Data pipelines","AI/ML infrastructure","LLMs","Vector databases","Agentic frameworks"],"x-skills-preferred":[],"datePosted":"2026-04-18T16:01:14.176Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"React, TypeScript, Python, Distributed systems, Data pipelines, AI/ML infrastructure, LLMs, Vector databases, Agentic frameworks","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":216000,"maxValue":270000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_d46c1e8f-b8c"},"title":"Strategic Deals Lead, Compute & Infrastructure","description":"<p>We are seeking a Strategic Deals Lead, Compute &amp; 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>As a key member of our team, 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.</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 modelling, 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>Analyse 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 centre/infrastructure)</li>\n</ul>\n<ul>\n<li>Background in cloud computing, data centre infrastructure, compute/silicon development, or technology-focused investment banking or consulting</li>\n</ul>\n<ul>\n<li>Familiarity with data centre infrastructure, compute hardware, and/or silicon development cycles</li>\n</ul>\n<ul>\n<li>Comfort with financial analysis and modelling; 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 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_d46c1e8f-b8c","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/5169670008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$250,000-$310,000 USD","x-skills-required":["Technical product/program management","Business development","Strategic partnerships","Cloud computing","Data centre infrastructure","Compute/silicon development","Financial analysis and modelling","Vendor financing arrangements"],"x-skills-preferred":["Experience structuring and negotiating strategic customer deals or partnerships","Background in technology-focused investment banking or consulting","Familiarity with data centre infrastructure, compute hardware, and/or silicon development cycles","Understanding of AI/ML infrastructure requirements and compute capacity planning","Experience with vendor financing, equipment leasing, or infrastructure investment analysis"],"datePosted":"2026-04-18T16:00:33.921Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Technical product/program management, Business development, Strategic partnerships, Cloud computing, Data centre infrastructure, Compute/silicon development, Financial analysis and modelling, Vendor financing arrangements, Experience structuring and negotiating strategic customer deals or partnerships, Background in technology-focused investment banking or consulting, Familiarity with data centre infrastructure, compute hardware, and/or silicon development cycles, Understanding of AI/ML infrastructure requirements and compute capacity planning, Experience with vendor financing, equipment leasing, or infrastructure investment analysis","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":250000,"maxValue":310000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_5cf5141e-a21"},"title":"Distinguished Engineer","description":"<p>We&#39;re seeking a Distinguished Engineer to shape the vision and technical roadmap of our core AI/ML infrastructure. Reporting directly to the SVP of Engineering, Enterprise AI, this individual will drive long-term technical direction for our Scale Generative AI Platform (SGP), influence architectural decisions across the company, and partner closely with engineering and product leaders to bring advanced AI capabilities to enterprise customers.</p>\n<p>You&#39;ll serve as a cross-organizational thought leader - setting standards for technical excellence, mentoring senior engineers, and ensuring our systems and models meet the demands of global-scale deployment. This is a rare opportunity to influence both foundational AI infrastructure and the enterprise AI applications built on top of it.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Define and drive the technical strategy for Scale&#39;s AI/ML infrastructure and SGP platform, balancing short and long-term investments.</li>\n<li>Partner with senior engineering and product leadership to ensure scalable, secure, and performant enterprise AI systems.</li>\n<li>Lead architecture and design reviews across multiple teams, ensuring technical consistency and innovation.</li>\n<li>Serve as a trusted advisor and mentor to principal engineers and technical leads across the organization.</li>\n<li>Evaluate and integrate emerging technologies in AI, distributed systems, and data infrastructure to keep Scale at the frontier of innovation.</li>\n<li>Represent Scale externally in the AI community - through speaking engagements, partnerships, and thought leadership.</li>\n<li>Drive technical execution and accountability for critical cross-functional initiatives that advance Scale&#39;s enterprise AI capabilities.</li>\n</ul>\n<p>Qualifications:</p>\n<ul>\n<li>15+ years of experience as a technical software engineering leader.</li>\n<li>Proven record of technical leadership at AI-native companies, hyperscalers, or equivalent high-scale environments.</li>\n<li>Deep technical expertise in AI/ML infrastructure, knowledge of ML models/algorithm design/implementation and their application to real-world problems; experience with GenAI preferred.</li>\n<li>Demonstrated success in setting technical vision and leading cross-organizational initiatives with measurable business impact.</li>\n<li>Experience influencing and mentoring engineering teams in complex, matrixed environments.</li>\n<li>Ability to communicate and collaborate effectively to create a shared sense of vision or purpose cross-team and cross-functionality.</li>\n<li>Advanced degree in Computer Science, Engineering, or related field preferred but not required.</li>\n</ul>\n<p>Culture &amp; Impact:</p>\n<p>At Scale, we believe that AI should amplify human potential - and our engineering culture reflects that belief. Our teams operate at the intersection of innovation, rigor, and impact, solving some of the hardest problems in AI infrastructure and deployment.</p>\n<p>The Distinguished Engineer will play a key role in shaping how AI systems are built, deployed, and governed within enterprise environments. This role represents the highest bar of technical excellence at Scale - a trusted voice in setting direction, enabling innovation, and ensuring that our technology scales responsibly and effectively to meet the evolving needs of our customers.</p>\n<p>You’ll have the opportunity to influence company-wide strategy, contribute to industry-leading work in generative AI infrastructure, and mentor the next generation of engineering talent pushing the boundaries of what’s possible with AI.</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_5cf5141e-a21","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Scale AI","sameAs":"https://scale.com/","logo":"https://logos.yubhub.co/scale.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/scaleai/jobs/4632142005","x-work-arrangement":"hybrid","x-experience-level":"executive","x-job-type":"full-time","x-salary-range":"$285,200-$356,500 USD","x-skills-required":["AI/ML infrastructure","Generative AI","Distributed systems","Data infrastructure","Technical leadership","Cross-functional collaboration","Communication","Mentoring"],"x-skills-preferred":[],"datePosted":"2026-04-18T16:00:20.293Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA; New York, NY"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"AI/ML infrastructure, Generative AI, Distributed systems, Data infrastructure, Technical leadership, Cross-functional collaboration, Communication, Mentoring","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":285200,"maxValue":356500,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_cd3b618b-96d"},"title":"Security Labs Engineer","description":"<p>Job Title: Security Labs Engineer</p>\n<p>About Anthropic</p>\n<p>Anthropic&#39;s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole.</p>\n<p>About the Role</p>\n<p>Security at Anthropic is not a compliance exercise. It is a core part of how we stay safe as we build increasingly capable systems. Our Responsible Scaling Policy commits us to launching structured security R&amp;D projects: ambitious, time-boxed experiments designed to resolve high-uncertainty questions about our long-term security posture.</p>\n<p>Each project runs for roughly 6 months with defined exit criteria. Some will succeed and move toward production. Others will fail, and we&#39;ll treat that as useful signals. The questions these projects are designed to answer include:</p>\n<ul>\n<li>Can our core research workflows survive extreme isolation?</li>\n</ul>\n<ul>\n<li>Can we get cryptographic guarantees where we currently rely on trust?</li>\n</ul>\n<ul>\n<li>Can AI become our most effective security control?</li>\n</ul>\n<p>As a Security Labs Engineer, you own one or more projects end-to-end: scoping the experiment, building the infrastructure, coordinating across teams, running the pilot, documenting results, and where the experiment succeeds, helping scale it into production. This is 0-to-1 and 1-to-10 work.</p>\n<p>Current Project Areas</p>\n<p>The portfolio evolves based on what we learn. Current areas include:</p>\n<ul>\n<li>Designing and operating a mock high-assurance research environment: simulating what our infrastructure would look like under extreme isolation and physical security controls, with real measurement of productivity impact</li>\n</ul>\n<ul>\n<li>Exploring cryptographic verification of model integrity using techniques like zero-knowledge proofs to provide mathematical guarantees about what is running in production</li>\n</ul>\n<ul>\n<li>Assessing the feasibility of confidential computing across the full model lifecycle (note: this is an open question, not a committed roadmap item)</li>\n</ul>\n<ul>\n<li>Piloting AI-assisted security tooling including vulnerability discovery, automated patching, anomaly detection, and adaptive behavioral monitoring</li>\n</ul>\n<ul>\n<li>Prototyping API-only access regimes where even internal research workflows never touch raw model weights</li>\n</ul>\n<p>Part of your job is helping shape what comes next based on gaps uncovered in the current round.</p>\n<p>Responsibilities</p>\n<ul>\n<li>Own the end-to-end execution of a Security Labs project: refine the hypothesis, design the experiment, build the prototype, run the pilot, and write up the results</li>\n</ul>\n<ul>\n<li>Build novel security infrastructure under real time pressure: isolated clusters, hardened access controls, cryptographic verification layers, with a bias toward learning fast</li>\n</ul>\n<ul>\n<li>Where experiments succeed, drive them toward production scale. An experiment that works on one cluster but not a hundred is not a finished result.</li>\n</ul>\n<ul>\n<li>Work embedded with research teams (Pretraining, RL, Inference) to stress-test whether their core workflows can function under extreme security controls, and document precisely where they break</li>\n</ul>\n<ul>\n<li>Evaluate and integrate emerging security technologies through coordination with external vendors and research groups</li>\n</ul>\n<ul>\n<li>Turn experimental results into clear, decision-ready writeups that inform Anthropic&#39;s long-term security architecture and RSP commitments</li>\n</ul>\n<ul>\n<li>Maintain a pain-point registry and feasibility assessment for each project, feeding directly into the design of production high-assurance environments</li>\n</ul>\n<ul>\n<li>Help scope and prioritize the next wave of Labs projects based on what the current round uncovers</li>\n</ul>\n<p>Requirements</p>\n<ul>\n<li>7+ years of software or security engineering experience, with a solid foundation in production systems</li>\n</ul>\n<ul>\n<li>Some of that time spent on pilots, prototypes, or applied research work where shipping a working answer to a hard question was the explicit goal</li>\n</ul>\n<ul>\n<li>Strong programming skills in Python and at least one systems language (Go, Rust, or C/C++)</li>\n</ul>\n<ul>\n<li>Hands-on experience with cloud infrastructure (AWS, GCP, or Azure), Kubernetes, and networking fundamentals sufficient to stand up and tear down isolated environments quickly</li>\n</ul>\n<ul>\n<li>A track record of cross-functional execution: you can walk into a room with ML researchers, infrastructure engineers, and vendors and leave with a shared plan</li>\n</ul>\n<ul>\n<li>Clear written communication: you know how to turn six weeks of experimentation into a two-page memo someone can act on</li>\n</ul>\n<ul>\n<li>Comfort with ambiguity and iteration, having run experiments that failed, extracted the lesson, and moved forward</li>\n</ul>\n<ul>\n<li>Genuine curiosity about what it would actually take to defend against a nation-state-level adversary</li>\n</ul>\n<ul>\n<li>Passion for AI safety and a real understanding of the role security plays in making frontier AI development go well</li>\n</ul>\n<ul>\n<li>Bachelor&#39;s degree in Computer Science, a related field, or equivalent industry experience required.</li>\n</ul>\n<p>Preferred Qualifications</p>\n<ul>\n<li>Prior experience in offensive security, red teaming, or security research, having thought adversarially about systems and knowing which threats actually matter</li>\n</ul>\n<ul>\n<li>Familiarity with airgapped or high-side environments (classified networks, ICS/SCADA, financial trading infrastructure, or similar) and the operational realities of working inside them</li>\n</ul>\n<ul>\n<li>Knowledge of applied cryptography: zero-knowledge proofs, attestation protocols, secure enclaves, TPMs, or confidential computing primitives</li>\n</ul>\n<ul>\n<li>Experience with ML infrastructure (training pipelines, inference serving, model packaging) sufficient for grounded conversations with researchers about what their workflows actually need</li>\n</ul>\n<ul>\n<li>Background building or operating security systems in environments that demand rapid iteration rather than rigid change control</li>\n</ul>\n<ul>\n<li>Prior work at a startup, on an innovation team, or in an applied research group where shipping a working v0 to answer a real question was explicitly the goal</li>\n</ul>\n<p>Location</p>\n<p>This role is based in our San Francisco office (500 Howard St). Several Labs projects involve physical secure facilities on-site, so expect to be in-office more frequently than Anthropic&#39;s standard 25% hybrid baseline.</p>\n<p>What We Offer</p>\n<ul>\n<li>Competitive salary and equity package</li>\n</ul>\n<ul>\n<li>Comprehensive health insurance and retirement plans</li>\n</ul>\n<ul>\n<li>Flexible work arrangements, including remote work options</li>\n</ul>\n<ul>\n<li>Professional development opportunities, including training and conference attendance</li>\n</ul>\n<ul>\n<li>Collaborative and dynamic work environment</li>\n</ul>\n<ul>\n<li>Access to cutting-edge technology and resources</li>\n</ul>\n<ul>\n<li>Opportunity to work on challenging and impactful projects</li>\n</ul>\n<ul>\n<li>Recognition and rewards for outstanding performance</li>\n</ul>\n<p>If you&#39;re excited about the opportunity to join our team and contribute to the development of secure and beneficial AI systems, please submit your application. We can&#39;t wait to hear from you!</p>\n<p>Deadline to Apply</p>\n<p>None, applications will be received on a rolling basis.</p>\n<p>Annual Compensation Range</p>\n<p>$405,000 - $485,000 USD</p>\n<p>Logistics</p>\n<p>Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience</p>\n<p>Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience</p>\n<p>Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position</p>\n<p>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.</p>\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 the process.</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_cd3b618b-96d","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/5153564008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$405,000 - $485,000 USD","x-skills-required":["Python","Go","Rust","C/C++","Cloud infrastructure","Kubernetes","Networking fundamentals","Cross-functional execution","Clear written communication","Comfort with ambiguity and iteration","Genuine curiosity about what it would actually take to defend against a nation-state-level adversary","Passion for AI safety","Real understanding of the role security plays in making frontier AI development go well"],"x-skills-preferred":["Offensive security","Red teaming","Security research","Applied cryptography","ML infrastructure","Background building or operating security systems in environments that demand rapid iteration rather than rigid change control","Prior work at a startup, on an innovation team, or in an applied research group where shipping a working v0 to answer a real question was explicitly the goal"],"datePosted":"2026-04-18T15:58:53.437Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, Go, Rust, C/C++, Cloud infrastructure, Kubernetes, Networking fundamentals, Cross-functional execution, Clear written communication, Comfort with ambiguity and iteration, Genuine curiosity about what it would actually take to defend against a nation-state-level adversary, Passion for AI safety, Real understanding of the role security plays in making frontier AI development go well, Offensive security, Red teaming, Security research, Applied cryptography, ML infrastructure, Background building or operating security systems in environments that demand rapid iteration rather than rigid change control, Prior work at a startup, on an innovation team, or in an applied research group where shipping a working v0 to answer a real question was explicitly the goal","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":405000,"maxValue":485000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_b79d9627-55a"},"title":"Research Engineer, Infrastructure, Training Systems","description":"<p>We&#39;re seeking an infrastructure research engineer to design and build scalable, efficient training systems for large models. As a key member of our team, you&#39;ll take ownership of the training stack end-to-end, ensuring every GPU cycle drives scientific progress. Your goal is to make experimentation and training at Thinking Machines fast and reliable, allowing our research teams to focus on science, not system bottlenecks.</p>\n<p>Key responsibilities include designing, implementing, and optimizing distributed training systems, developing high-performance optimizations, and establishing standards for reliability, maintainability, and security. You&#39;ll collaborate with researchers and engineers to build scalable infrastructure and publish learnings through internal documentation, open-source libraries, or technical reports.</p>\n<p>We&#39;re looking for someone who blends deep systems and performance expertise with a curiosity for machine learning at scale. A strong understanding of deep learning frameworks, such as PyTorch, and experience working on distributed training for large models are preferred. If you have a track record of improving research productivity through infrastructure design or process improvements, that&#39;s a plus.</p>\n<p>This role is based in San Francisco, California, and offers a competitive salary range of $350,000 - $475,000 USD per year, depending on background, skills, and experience. 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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. 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It is a core part of how we stay safe as we build increasingly capable systems. Our Responsible Scaling Policy commits us to launching structured security R&amp;D projects: ambitious, time-boxed experiments designed to resolve high-uncertainty questions about our long-term security posture.</p>\n<p>Each project runs for roughly 6 months with defined exit criteria. Some will succeed and move toward production. Others will fail, and we&#39;ll treat that as useful signals. The questions these projects are designed to answer include:</p>\n<ul>\n<li>Can our core research workflows survive extreme isolation?</li>\n<li>Can we get cryptographic guarantees where we currently rely on trust?</li>\n<li>Can AI become our most effective security control?</li>\n</ul>\n<p>As a Security Labs Engineer, you own one or more projects end-to-end: scoping the experiment, building the infrastructure, coordinating across teams, running the pilot, documenting results, and where the experiment succeeds, helping scale it into production. This is 0-to-1 and 1-to-10 work.</p>\n<p><strong>Current Project Areas</strong></p>\n<p>The portfolio evolves based on what we learn. Current areas include:</p>\n<ul>\n<li>Designing and operating a mock high-assurance research environment: simulating what our infrastructure would look like under extreme isolation and physical security controls, with real measurement of productivity impact</li>\n<li>Exploring cryptographic verification of model integrity using techniques like zero-knowledge proofs to provide mathematical guarantees about what is running in production</li>\n<li>Assessing the feasibility of confidential computing across the full model lifecycle (note: this is an open question, not a committed roadmap item)</li>\n<li>Piloting AI-assisted security tooling including vulnerability discovery, automated patching, anomaly detection, and adaptive behavioral monitoring</li>\n<li>Prototyping API-only access regimes where even internal research workflows never touch raw model weights</li>\n</ul>\n<p>Part of your job is helping shape what comes next based on gaps uncovered in the current round.</p>\n<p><strong>Responsibilities</strong></p>\n<ul>\n<li>Own the end-to-end execution of a Security Labs project: refine the hypothesis, design the experiment, build the prototype, run the pilot, and write up the results</li>\n<li>Build novel security infrastructure under real time pressure: isolated clusters, hardened access controls, cryptographic verification layers, with a bias toward learning fast</li>\n<li>Where experiments succeed, drive them toward production scale. An experiment that works on one cluster but not a hundred is not a finished result.</li>\n<li>Work embedded with research teams (Pretraining, RL, Inference) to stress-test whether their core workflows can function under extreme security controls, and document precisely where they break</li>\n<li>Evaluate and integrate emerging security technologies through coordination with external vendors and research groups</li>\n<li>Turn experimental results into clear, decision-ready writeups that inform Anthropic&#39;s long-term security architecture and RSP commitments</li>\n<li>Maintain a pain-point registry and feasibility assessment for each project, feeding directly into the design of production high-assurance environments</li>\n<li>Help scope and prioritize the next wave of Labs projects based on what the current round uncovers</li>\n</ul>\n<p><strong>Requirements</strong></p>\n<ul>\n<li>7+ years of software or security engineering experience, with a solid foundation in production systems</li>\n<li>Some of that time spent on pilots, prototypes, or applied research work where shipping a working answer to a hard question was the explicit goal</li>\n<li>Strong programming skills in Python and at least one systems language (Go, Rust, or C/C++)</li>\n<li>Hands-on experience with cloud infrastructure (AWS, GCP, or Azure), Kubernetes, and networking fundamentals sufficient to stand up and tear down isolated environments quickly</li>\n<li>A track record of cross-functional execution: you can walk into a room with ML researchers, infrastructure engineers, and vendors and leave with a shared plan</li>\n<li>Clear written communication: you know how to turn six weeks of experimentation into a two-page memo someone can act on</li>\n<li>Comfort with ambiguity and iteration, having run experiments that failed, extracted the lesson, and moved forward</li>\n<li>Genuine curiosity about what it would actually take to defend against a nation-state-level adversary</li>\n<li>Passion for AI safety and a real understanding of the role security plays in making frontier AI development go well</li>\n<li>Bachelor&#39;s degree in Computer Science, a related field, or equivalent industry experience required.</li>\n</ul>\n<p><strong>Nice to Have</strong></p>\n<ul>\n<li>Prior experience in offensive security, red teaming, or security research, having thought adversarially about systems and knowing which threats actually matter</li>\n<li>Familiarity with airgapped or high-side environments (classified networks, ICS/SCADA, financial trading infrastructure, or similar) and the operational realities of working inside them</li>\n<li>Knowledge of applied cryptography: zero-knowledge proofs, attestation protocols, secure enclaves, TPMs, or confidential computing primitives</li>\n<li>Experience with ML infrastructure (training pipelines, inference serving, model packaging) sufficient for grounded conversations with researchers about what their workflows actually need</li>\n<li>Background building or operating security systems in environments that demand rapid iteration rather than rigid change control</li>\n<li>Prior work at a startup, on an innovation team, or in an applied research group where shipping a working v0 to answer a real question was explicitly the goal</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_6e48ec86-b97","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/5153564008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$405,000-$485,000 USD","x-skills-required":["Python","Go","Rust","C/C++","Cloud infrastructure","Kubernetes","Networking fundamentals","Cross-functional execution","Clear written communication","Ambiguity and iteration","Genuine curiosity","Passion for AI safety"],"x-skills-preferred":["Offensive security","Red teaming","Security research","Applied cryptography","ML infrastructure","Secure enclaves","TPMs","Confidential computing primitives"],"datePosted":"2026-04-18T15:45:04.027Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, Go, Rust, C/C++, Cloud infrastructure, Kubernetes, Networking fundamentals, Cross-functional execution, Clear written communication, Ambiguity and iteration, Genuine curiosity, Passion for AI safety, Offensive security, Red teaming, Security research, Applied cryptography, ML infrastructure, Secure enclaves, TPMs, Confidential computing primitives","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":405000,"maxValue":485000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_bd9625d9-99b"},"title":"ML Infrastructure Engineer, Safeguards","description":"<p>We are seeking a Machine Learning Infrastructure Engineer to join our Safeguards organization, where you&#39;ll build and scale the critical infrastructure that powers our AI safety systems.</p>\n<p>As part of the Safeguards team, you&#39;ll design and implement ML infrastructure that powers Claude safety. Your work will directly contribute to making AI systems more trustworthy and aligned with human values, ensuring our models operate safely as they become more capable.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Design and build scalable ML infrastructure to support real-time and batch classifier and safety evaluations across our model ecosystem</li>\n<li>Build monitoring and observability tools to track model performance, data quality, and system health for safety-critical applications</li>\n<li>Collaborate with research teams to productionize safety research, translating experimental safety techniques into robust, scalable systems</li>\n<li>Optimize inference latency and throughput for real-time safety evaluations while maintaining high reliability standards</li>\n<li>Implement automated testing, deployment, and rollback systems for ML models in production safety applications</li>\n<li>Partner with Safeguards, Security, and Alignment teams to understand requirements and deliver infrastructure that meets safety and production needs</li>\n<li>Contribute to the development of internal tools and frameworks that accelerate safety research and deployment</li>\n</ul>\n<p>You may be a good fit if you:</p>\n<ul>\n<li>Have 5+ years of experience building production ML infrastructure, ideally in safety-critical domains like fraud detection, content moderation, or risk assessment</li>\n<li>Are proficient in Python and have experience with ML frameworks like PyTorch, TensorFlow, or JAX</li>\n<li>Have hands-on experience with cloud platforms (AWS, GCP) and container orchestration (Kubernetes)</li>\n<li>Understand distributed systems principles and have built systems that handle high-throughput, low-latency workloads</li>\n<li>Have experience with data engineering tools and building robust data pipelines (e.g., Spark, Airflow, streaming systems)</li>\n<li>Are results-oriented, with a bias towards reliability and impact in safety-critical systems</li>\n<li>Enjoy collaborating with researchers and translating cutting-edge research into production systems</li>\n<li>Care deeply about AI safety and the societal impacts of your work</li>\n</ul>\n<p>Strong candidates may have experience with:</p>\n<ul>\n<li>Working with large language models and modern transformer architectures</li>\n<li>Implementing A/B testing frameworks and experimentation infrastructure for ML systems</li>\n<li>Developing monitoring and alerting systems for ML model performance and data drift</li>\n<li>Building automated labeling systems and human-in-the-loop workflows</li>\n<li>Experience in trust &amp; safety, fraud prevention, or content moderation domains</li>\n<li>Knowledge of privacy-preserving ML techniques and compliance requirements</li>\n<li>Contributing to open-source ML infrastructure projects</li>\n</ul>\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.</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_bd9625d9-99b","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/4778843008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$320,000-$405,000 USD","x-skills-required":["Python","PyTorch","TensorFlow","JAX","Cloud platforms (AWS, GCP)","Container orchestration (Kubernetes)","Distributed systems principles","Data engineering tools (Spark, Airflow, streaming systems)"],"x-skills-preferred":["Large language models and modern transformer architectures","A/B testing frameworks and experimentation infrastructure for ML systems","Monitoring and alerting systems for ML model performance and data drift","Automated labeling systems and human-in-the-loop workflows","Trust & safety, fraud prevention, or content moderation domains","Privacy-preserving ML techniques and compliance requirements","Open-source ML infrastructure projects"],"datePosted":"2026-04-18T15:44:06.907Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, PyTorch, TensorFlow, JAX, Cloud platforms (AWS, GCP), Container orchestration (Kubernetes), Distributed systems principles, Data engineering tools (Spark, Airflow, streaming systems), Large language models and modern transformer architectures, A/B testing frameworks and experimentation infrastructure for ML systems, Monitoring and alerting systems for ML model performance and data drift, Automated labeling systems and human-in-the-loop workflows, Trust & safety, fraud prevention, or content moderation domains, Privacy-preserving ML techniques and compliance requirements, Open-source ML infrastructure projects","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":320000,"maxValue":405000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_cbaf9906-291"},"title":"Platform Hardware Security","description":"<p>We&#39;re seeking a Platform Hardware Security Engineer to design and implement security architectures for bare-metal infrastructure. You&#39;ll work with teams across Anthropic to build firmware, bootloaders, operating systems, and attestation systems to ensure the integrity of our infrastructure from the ground up.</p>\n<p>This role requires expertise in low-level systems security and the ability to architect solutions that balance security requirements with the performance demands of training AI models across our massive fleet.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Design and implement secure boot chains from firmware through OS initialization for diverse hardware platforms (CPUs, BMCs, switches, peripherals, and embedded microcontrollers)</li>\n</ul>\n<ul>\n<li>Architect attestation systems that provide cryptographic proof of system state from hardware root of trust through application layer</li>\n</ul>\n<ul>\n<li>Develop measured boot implementations and runtime integrity monitoring</li>\n</ul>\n<ul>\n<li>Create reference architectures and security requirements for bare-metal deployments</li>\n</ul>\n<ul>\n<li>Integrate security controls with infrastructure teams without impacting training performance</li>\n</ul>\n<ul>\n<li>Prototype and validate security mechanisms before production deployment</li>\n</ul>\n<ul>\n<li>Conduct firmware vulnerability assessments and penetration testing</li>\n</ul>\n<ul>\n<li>Build firmware analysis pipelines for continuous security monitoring</li>\n</ul>\n<ul>\n<li>Document security architectures and maintain threat models</li>\n</ul>\n<ul>\n<li>Collaborate with software and hardware vendors to ensure security capabilities meet our requirements</li>\n</ul>\n<p>Who you are:</p>\n<ul>\n<li>8+ years of experience in systems security, with at least 5 years focused on firmware and hardware security (firmware, bootloaders, and OS-level security)</li>\n</ul>\n<ul>\n<li>Hands-on experience with secure boot, measured boot, and attestation technologies (TPM, Intel TXT, AMD SEV, ARM TrustZone)</li>\n</ul>\n<ul>\n<li>Strong understanding of cryptographic protocols and hardware security modules</li>\n</ul>\n<ul>\n<li>Experience with UEFI/BIOS or embedded firmware security, bootloader hardening, and chain of trust implementation</li>\n</ul>\n<ul>\n<li>Proficiency in low-level programming (C, Rust, Assembly) and systems programming</li>\n</ul>\n<ul>\n<li>Knowledge of firmware vulnerability assessment and threat modeling</li>\n</ul>\n<ul>\n<li>Track record of designing security architectures for complex, distributed systems</li>\n</ul>\n<ul>\n<li>Experience with supply chain security</li>\n</ul>\n<ul>\n<li>Ability to work effectively across hardware and software boundaries</li>\n</ul>\n<ul>\n<li>Knowledge of NIST firmware security guidelines and hardware security frameworks</li>\n</ul>\n<p>Strong candidates may also have:</p>\n<ul>\n<li>Experience with confidential computing technologies and hardware-based TEEs</li>\n</ul>\n<ul>\n<li>Knowledge of SLSA framework and software supply chain security standards</li>\n</ul>\n<ul>\n<li>Experience securing large-scale HPC or cloud infrastructure</li>\n</ul>\n<ul>\n<li>Contributions to open-source security projects (coreboot, CHIPSEC, etc.)</li>\n</ul>\n<ul>\n<li>Background in formal verification or security proof techniques</li>\n</ul>\n<ul>\n<li>Experience with silicon root of trust implementations</li>\n</ul>\n<ul>\n<li>Experience working with building foundational technical designs, operational leadership, and vendor collaboration</li>\n</ul>\n<ul>\n<li>Previous work with AI/ML infrastructure security</li>\n</ul>\n<p>Annual Salary: $405,000-$485,000 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<ul>\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>Why work with us?</p>\n<ul>\n<li>Competitive compensation and benefits</li>\n</ul>\n<ul>\n<li>Optional equity donation matching</li>\n</ul>\n<ul>\n<li>Generous vacation and parental leave</li>\n</ul>\n<ul>\n<li>Flexible working hours</li>\n</ul>\n<ul>\n<li>Lovely office space in which to collaborate with colleagues</li>\n</ul>\n<p>Guidance on Candidates&#39; AI Usage: Learn about our policy for using AI in our application process</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_cbaf9906-291","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/4929689008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$405,000-$485,000 USD","x-skills-required":["Secure boot","Measured boot","Attestation technologies","Cryptographic protocols","Hardware security modules","UEFI/BIOS or embedded firmware security","Bootloader hardening","Chain of trust implementation","Low-level programming","Systems programming","Firmware vulnerability assessment","Threat modeling","Supply chain security","NIST firmware security guidelines","Hardware security frameworks"],"x-skills-preferred":["Confidential computing technologies","Hardware-based TEEs","SLSA framework","Software supply chain security standards","Large-scale HPC or cloud infrastructure","Open-source security projects","Formal verification","Security proof techniques","Silicon root of trust implementations","Vendor collaboration","AI/ML infrastructure security"],"datePosted":"2026-04-18T15:43:00.394Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"New York City, NY | Seattle, WA; San Francisco, CA | New York City, NY | Seattle, WA; Washington, DC"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Secure boot, Measured boot, Attestation technologies, Cryptographic protocols, Hardware security modules, UEFI/BIOS or embedded firmware security, Bootloader hardening, Chain of trust implementation, Low-level programming, Systems programming, Firmware vulnerability assessment, Threat modeling, Supply chain security, NIST firmware security guidelines, Hardware security frameworks, Confidential computing technologies, Hardware-based TEEs, SLSA framework, Software supply chain security standards, Large-scale HPC or cloud infrastructure, Open-source security projects, Formal verification, Security proof techniques, Silicon root of trust implementations, Vendor collaboration, AI/ML infrastructure security","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":405000,"maxValue":485000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_3b359ef2-6f8"},"title":"Machine Learning Systems Engineer, Research Tools","description":"<p>We are seeking an experienced Machine Learning Systems Engineer to join our Encodings and Tokenization team at Anthropic. This cross-functional role will be instrumental in developing and optimizing the encodings and tokenization systems used throughout our Finetuning workflows. As a bridge between our Pretraining and Finetuning teams, you&#39;ll build critical infrastructure that directly impacts how our models learn from and interpret data.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Design, develop, and maintain tokenization systems used across Pretraining and Finetuning workflows</li>\n<li>Optimize encoding techniques to improve model training efficiency and performance</li>\n<li>Collaborate closely with research teams to understand their evolving needs around data representation</li>\n<li>Build infrastructure that enables researchers to experiment with novel tokenization approaches</li>\n<li>Implement systems for monitoring and debugging tokenization-related issues in the model training pipeline</li>\n<li>Create robust testing frameworks to validate tokenization systems across diverse languages and data types</li>\n<li>Identify and address bottlenecks in data processing pipelines related to tokenization</li>\n<li>Document systems thoroughly and communicate technical decisions clearly to stakeholders across teams</li>\n</ul>\n<p>You May Be a Good Fit If You:</p>\n<ul>\n<li>Have significant software engineering experience with demonstrated machine learning expertise</li>\n<li>Are comfortable navigating ambiguity and developing solutions in rapidly evolving research environments</li>\n<li>Can work independently while maintaining strong collaboration with cross-functional teams</li>\n<li>Are results-oriented, with a bias towards flexibility and impact</li>\n<li>Have experience with machine learning systems, data pipelines, or ML infrastructure</li>\n<li>Are proficient in Python and familiar with modern ML development practices</li>\n<li>Have strong analytical skills and can evaluate the impact of engineering changes on research outcomes</li>\n<li>Pick up slack, even if it goes outside your job description</li>\n<li>Enjoy pair programming (we love to pair!)</li>\n<li>Care about the societal impacts of your work and are committed to developing AI responsibly</li>\n</ul>\n<p>Strong Candidates May Also Have Experience With:</p>\n<ul>\n<li>Working with machine learning data processing pipelines</li>\n<li>Building or optimizing data encodings for ML applications</li>\n<li>Implementing or working with BPE, WordPiece, or other tokenization algorithms</li>\n<li>Performance optimization of ML data processing systems</li>\n<li>Multi-language tokenization challenges and solutions</li>\n<li>Research environments where engineering directly enables scientific progress</li>\n<li>Distributed systems and parallel computing for ML workflows</li>\n<li>Large language models or other transformer-based architectures (not required)</li>\n</ul>\n<p>The annual compensation range for this role is $320,000-$405,000 USD.</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_3b359ef2-6f8","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/4952079008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$320,000-$405,000 USD","x-skills-required":["Machine Learning","Software Engineering","Python","Data Pipelines","ML Infrastructure"],"x-skills-preferred":["BPE","WordPiece","Tokenization Algorithms","Performance Optimization","Distributed Systems"],"datePosted":"2026-04-18T15:42:42.125Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA | New York City, NY | Seattle, WA"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Machine Learning, Software Engineering, Python, Data Pipelines, ML Infrastructure, BPE, WordPiece, Tokenization Algorithms, Performance Optimization, Distributed Systems","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":320000,"maxValue":405000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_022d9aef-8cd"},"title":"Member of Technical Staff - Infrastructure Reliability","description":"<p><strong>About the Role</strong></p>\n<p>We are training some of the largest models in the world on the latest hardware across multiple environments. To do this reliably at xAI&#39;s pace, we need engineers who have battle-tested experience keeping massive distributed infrastructure up and running 24/7, including on-prem and cloud-based infrastructure.</p>\n<p>You will own the availability, performance, and evolution of xAI&#39;s core compute, storage, and networking infrastructure. This is not an ops-only role , strong coding is a hard requirement. You will design, implement, and ship systems software, automation, and tooling in Python and/or Rust that directly impact training throughput and cluster utilization.</p>\n<p><strong>Responsibilities</strong></p>\n<ul>\n<li>Define and execute the technical strategy for infrastructure reliability and scalability</li>\n<li>Build and maintain the automation, observability, and control planes that keep multi-datacenter, hybrid cloud/on-prem environments healthy</li>\n<li>Lead incident response, deep-dive root cause analysis, and post-mortems that drive real fixes</li>\n<li>Identify, instrument, and eliminate systemic failure patterns (capacity, network, hardware, storage, software)</li>\n<li>Design and implement high-leverage systems software (daemons, controllers, schedulers, etc.) in Python and Rust.</li>\n</ul>\n<p><strong>Basic Qualifications</strong></p>\n<ul>\n<li>5+ years shipping production software and/or operating distributed infrastructure at scale</li>\n<li>Expert-level knowledge of Linux systems, TCP/IP networking, and systems programming</li>\n<li>Strong coding skills with proven production experience in Rust (strongly preferred) and at least one of Python, Go, or C++.</li>\n</ul>\n<p><strong>Preferred Skills and Experience</strong></p>\n<ul>\n<li>Significant contributions to large-scale GPU clusters or AI/ML infrastructure</li>\n<li>Experience in on-call rotations and incident response in high-stakes environments.</li>\n</ul>\n<p><strong>Compensation and Benefits</strong></p>\n<p>$180,000 - $400,000 USD</p>\n<p>Base salary is just one part of our total rewards package at xAI, which also includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short &amp; long-term disability insurance, life insurance, and various other discounts and perks.</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_022d9aef-8cd","directApply":true,"hiringOrganization":{"@type":"Organization","name":"xAI","sameAs":"https://www.xai.com/","logo":"https://logos.yubhub.co/xai.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/xai/jobs/4801451007","x-work-arrangement":"onsite","x-experience-level":"staff","x-job-type":"full-time","x-salary-range":"$180,000 - $400,000 USD","x-skills-required":["Linux systems","TCP/IP networking","systems programming","Rust","Python","Go","C++","container orchestration","container runtimes","infrastructure-as-code"],"x-skills-preferred":["large-scale GPU clusters","AI/ML infrastructure","on-call rotations","incident response"],"datePosted":"2026-04-18T15:42:36.486Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Palo Alto, CA"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Linux systems, TCP/IP networking, systems programming, Rust, Python, Go, C++, container orchestration, container runtimes, infrastructure-as-code, large-scale GPU clusters, AI/ML infrastructure, on-call rotations, incident response","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":180000,"maxValue":400000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_9cd0420a-99d"},"title":"Network Engineer, Capacity and Efficiency","description":"<p><strong>About the Role</strong></p>\n<p>We&#39;re looking for a network engineer who thinks in metrics first. You will use deep networking knowledge and rigorous measurement to figure out where and how bandwidth, latency, and dollars are being used, find optimization opportunities and land them.</p>\n<p><strong>Responsibilities</strong></p>\n<ul>\n<li>Build the network observability stack. Design and deploy telemetry pipelines , sFlow/IPFIX, gNMI streaming, eBPF host probes , that turn packet counters into per-flow, per-tenant, per-workload cost and utilization data. Own the SLIs for backbone and DCN fabric health.</li>\n<li>Hunt for efficiency. Analyze inter-region traffic patterns, identify hot links and stranded capacity, and quantify the dollar impact. Build the models that tell us whether we should buy more capacity, or move the workload.</li>\n<li>Own QoS and traffic engineering. Design and operate traffic classification, marking, and shaping across the backbone. Make sure bulk checkpoint transfers don’t starve latency-sensitive inference, and that we’re not paying premium cross-region rates for traffic that could take the cheap path.</li>\n<li>Drive cost attribution. Tie network spend , egress, interconnect ports, transit, optical leases , back to the teams and workloads that generate it. Make network cost a first-class input to capacity planning and workload placement decisions.</li>\n<li>Influence decisions you don&#39;t own. A large fraction of this role is convincing other teams to act on what your data shows: making the case to research that a traffic pattern needs to change, to finance that an interconnect tranche is worth buying, to Systems Networking that a QoS policy needs rewriting.</li>\n</ul>\n<p><strong>Requirements</strong></p>\n<ul>\n<li>Have 5+ years operating large-scale production networks , data center fabrics (spine-leaf, Clos), backbone/WAN, or hyperscaler-adjacent environments.</li>\n<li>Are genuinely fluent across the stack: BGP (including policy and communities), ECMP, VXLAN/EVPN or equivalent overlays, QoS (DSCP, queuing, shaping), and L1/optical basics (DWDM, coherent, LAGs).</li>\n<li>Know at least one major CSP’s networking model deeply , AWS (VPC, TGW, Direct Connect, Gateway Load Balancer) or GCP (Shared VPC, Interconnect, Cloud Router, Network Connectivity Center) , and understand how their overlays interact with physical underlays.</li>\n<li>Have built or operated network telemetry at scale: streaming telemetry (gNMI/OpenConfig), flow export (sFlow, IPFIX, NetFlow), or eBPF-based host-side instrumentation. You can reason about sampling, cardinality, and storage tradeoffs.</li>\n<li>Comfortable writing Python or Go to build tooling, telemetry pipelines, infrastructure-as-code, config management for network devices and automation, that you’ll ship to production.</li>\n<li>Think quantitatively by default. You reach for a notebook or a Grafana query before you reach for an opinion, and you can turn messy counter data into a defensible cost model.</li>\n<li>Communicate crisply. You can explain to a finance partner why a 10% egress reduction matters, and to a network engineer why a specific ECMP imbalance is costing real money.</li>\n</ul>\n<p><strong>Nice to Have</strong></p>\n<ul>\n<li>SRE experience for large-scale network infrastructure , designing for reliability, defining SLOs/SLIs for network services, capacity planning with error budgets, and incident response for network-impacting outages at scale.</li>\n<li>Background on a cloud provider&#39;s networking team or a cloud networking product team , building or operating the interconnect, backbone, or SDN control plane from the provider side, not just consuming it as a customer.</li>\n<li>Familiarity with AI/ML infrastructure traffic patterns like collective communication (all-reduce, all-gather), checkpoint/weight transfer, inference serving, and how these stress networks differ than traditional workloads in terms of burst behavior, flow synchronization, and bandwidth symmetry.</li>\n<li>Experience with HPC fabrics like InfiniBand, RoCE v2, lossless Ethernet, or custom high-radix topologies and an understanding of how job placement, congestion management, and adaptive routing interact at scale.</li>\n<li>Background in traffic engineering for large backbones and the operational judgment to know when TE is worth the complexity.</li>\n<li>Hands-on time with multi-cloud connectivity: cross-cloud peering, private interconnect products, and the billing models that come with them.</li>\n<li>Experience building cost/chargeback systems for shared infrastructure, or FinOps exposure in a large cloud environment.</li>\n</ul>\n<p><strong>Representative Projects</strong></p>\n<ul>\n<li>Build a per-flow cost attribution pipeline that traces every byte of cross-region egress back to the team and workload that generated it</li>\n<li>Design QoS policy for the private backbone that prevents bulk checkpoint transfers from starving inference traffic</li>\n<li>Model whether it&#39;s cheaper to buy an additional 1.6Tb interconnect tranche or to re-route traffic through existing capacity</li>\n<li>Instrument DCN fabric utilization with streaming telemetry and build the Grafana dashboards that become the team&#39;s source of truth for network observability</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_9cd0420a-99d","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://anthropic.com","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/5177143008","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["network engineering","network observability","telemetry pipelines","sFlow/IPFIX","gNMI streaming","eBPF host probes","BGP","ECMP","VXLAN/EVPN","QoS","DSCP","queuing","shaping","L1/optical basics","DWDM","coherent","LAGs","AWS","GCP","cloud networking","infrastructure-as-code","config management","automation","Python","Go","quantitative analysis","cost modeling","communication"],"x-skills-preferred":["SRE","cloud provider's networking team","cloud networking product team","AI/ML infrastructure traffic patterns","HPC fabrics","traffic engineering","multi-cloud connectivity","cost/chargeback systems","FinOps"],"datePosted":"2026-04-18T15:42:29.482Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA | New York City, NY"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"network engineering, network observability, telemetry pipelines, sFlow/IPFIX, gNMI streaming, eBPF host probes, BGP, ECMP, VXLAN/EVPN, QoS, DSCP, queuing, shaping, L1/optical basics, DWDM, coherent, LAGs, AWS, GCP, cloud networking, infrastructure-as-code, config management, automation, Python, Go, quantitative analysis, cost modeling, communication, SRE, cloud provider's networking team, cloud networking product team, AI/ML infrastructure traffic patterns, HPC fabrics, traffic engineering, multi-cloud connectivity, cost/chargeback systems, FinOps"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_73e0f7a0-d1b"},"title":"Infrastructure Engineer, Sandboxing","description":"<p>We are seeking an experienced Infrastructure Engineer to join our Sandboxing team within the Research organization. In this role, you&#39;ll build and scale the systems that enable researchers to safely execute and experiment with AI-generated code and interactions in isolated environments.</p>\n<p>As our models become more capable, the infrastructure supporting secure execution environments becomes increasingly critical. You&#39;ll work on distributed systems that must operate reliably at significant scale while maintaining strong security boundaries. Your work will directly support Anthropic&#39;s mission to develop AI systems that are safe, beneficial, and trustworthy.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Design, build, and operate distributed backend systems that power secure sandboxed execution environments</li>\n<li>Scale infrastructure to meet growing research and product demands while maintaining reliability and performance</li>\n<li>Implement and maintain serverless architectures and container orchestration systems</li>\n<li>Collaborate with research teams to understand requirements and translate them into robust infrastructure solutions</li>\n<li>Develop monitoring, alerting, and observability systems to ensure operational excellence</li>\n<li>Participate in on-call rotations and incident response to maintain system reliability</li>\n<li>Contribute to infrastructure automation and tooling that improves developer productivity</li>\n<li>Partner with security teams to ensure sandboxing infrastructure maintains appropriate isolation guarantees</li>\n</ul>\n<p>You may be a good fit if you:</p>\n<ul>\n<li>Have 5+ years of experience building and operating backend infrastructure at scale</li>\n<li>Have deep expertise in distributed systems design and implementation</li>\n<li>Have strong operational experience, including debugging complex production issues</li>\n<li>Are proficient with cloud platforms, particularly GCP/GCS (experience with AWS or Azure is also valuable)</li>\n<li>Have experience with containerization technologies (Docker, Kubernetes) and understand their security implications</li>\n<li>Are comfortable working with infrastructure as code and modern DevOps practices</li>\n<li>Have strong programming skills in languages such as Python, Go, or Rust</li>\n<li>Are results-oriented with a bias towards flexibility and impact</li>\n<li>Care about the societal impacts of your work and are motivated by Anthropic&#39;s mission</li>\n</ul>\n<p>Strong candidates may also have experience with:</p>\n<ul>\n<li>Serverless architectures and functions-as-a-service platforms (Cloud Functions, Cloud Run, Lambda)</li>\n<li>Designing and implementing secure multi-tenant systems</li>\n<li>High-performance computing environments or ML infrastructure</li>\n<li>Linux systems internals, including namespaces, cgroups, and seccomp</li>\n<li>Network security and isolation techniques</li>\n<li>Building systems that support research workflows and rapid iteration</li>\n</ul>\n<p>The annual compensation range for this role is $300,000-$405,000 USD.</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.</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_73e0f7a0-d1b","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/5030680008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$300,000-$405,000 USD","x-skills-required":["distributed systems design and implementation","cloud platforms (GCP/GCS)","containerization technologies (Docker, Kubernetes)","infrastructure as code and modern DevOps practices","strong programming skills in languages such as Python, Go, or Rust"],"x-skills-preferred":["serverless architectures and functions-as-a-service platforms","secure multi-tenant systems","high-performance computing environments or ML infrastructure","Linux systems internals","network security and isolation techniques"],"datePosted":"2026-04-18T15:40:19.102Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA | New York City, NY | Seattle, WA"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"distributed systems design and implementation, cloud platforms (GCP/GCS), containerization technologies (Docker, Kubernetes), infrastructure as code and modern DevOps practices, strong programming skills in languages such as Python, Go, or Rust, serverless architectures and functions-as-a-service platforms, secure multi-tenant systems, high-performance computing environments or ML infrastructure, Linux systems internals, network security and isolation techniques","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_78a9b8f2-81c"},"title":"Senior Software Engineer - Data Infrastructure","description":"<p>We believe that the way people interact with their finances will drastically improve in the next few years. We&#39;re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products.</p>\n<p>Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use.</p>\n<p>Making data driven decisions is key to Plaid&#39;s culture. To support that, we need to scale our data systems while maintaining correct and complete data. We provide tooling and guidance to teams across engineering, product, and business and help them explore our data quickly and safely to get the data insights they need, which ultimately helps Plaid serve our customers more effectively.</p>\n<p><strong>Responsibilities</strong></p>\n<ul>\n<li>Contribute towards the long-term technical roadmap for data-driven and machine learning iteration at Plaid</li>\n<li>Leading key data infrastructure projects such as improving ML development golden paths, implementing offline streaming solutions for data freshness, building net new ETL pipeline infrastructure, and evolving data warehouse or data lakehouse capabilities.</li>\n<li>Working with stakeholders in other teams and functions to define technical roadmaps for key backend systems and abstractions across Plaid.</li>\n<li>Debugging, troubleshooting, and reducing operational burden for our Data Platform.</li>\n<li>Growing the team via mentorship and leadership, reviewing technical documents and code changes.</li>\n</ul>\n<p><strong>Qualifications</strong></p>\n<ul>\n<li>5+ years of software engineering experience</li>\n<li>Extensive hands-on software engineering experience, with a strong track record of delivering successful projects within the Data Infrastructure or Platform domain at similar or larger companies.</li>\n<li>Deep understanding of one of: ML Infrastructure systems, including Feature Stores, Training Infrastructure, Serving Infrastructure, and Model Monitoring OR Data Infrastructure systems, including Data Warehouses, Data Lakehouses, Apache Spark, Streaming Infrastructure, Workflow Orchestration.</li>\n<li>Strong cross-functional collaboration, communication, and project management skills, with proven ability to coordinate effectively.</li>\n<li>Proficiency in coding, testing, and system design, ensuring reliable and scalable solutions.</li>\n<li>Demonstrated leadership abilities, including experience mentoring and guiding junior engineers.</li>\n</ul>\n<p><strong>Additional Information</strong></p>\n<p>Our mission at Plaid is to unlock financial freedom for everyone. To support that mission, we seek to build a diverse team of driven individuals who care deeply about making the financial ecosystem more equitable.</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_78a9b8f2-81c","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Plaid","sameAs":"https://plaid.com/","logo":"https://logos.yubhub.co/plaid.com.png"},"x-apply-url":"https://jobs.lever.co/plaid/05b0ae3f-ec60-48d6-ae27-1bd89d928c47","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$190,800-$286,800 per year","x-skills-required":["ML Infrastructure systems","Data Infrastructure systems","Apache Spark","Streaming Infrastructure","Workflow Orchestration","Feature Stores","Training Infrastructure","Serving Infrastructure","Model Monitoring","Data Warehouses","Data Lakehouses"],"x-skills-preferred":[],"datePosted":"2026-04-17T12:51:58.720Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Finance","skills":"ML Infrastructure systems, Data Infrastructure systems, Apache Spark, Streaming Infrastructure, Workflow Orchestration, Feature Stores, Training Infrastructure, Serving Infrastructure, Model Monitoring, Data Warehouses, Data Lakehouses","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":190800,"maxValue":286800,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_1d67d51e-39e"},"title":"CyberSecurity, Offensive Security Engineer","description":"<p>At Mistral AI, we&#39;re pushing the boundaries of what&#39;s possible with agentic systems,building products like Mistral Studio and Mistral Vibe that redefine how users interact with AI.</p>\n<p>As a Security Researcher, you&#39;ll play a pivotal role in safeguarding these innovations by anticipating, identifying, and mitigating risks before they materialize. This isn&#39;t just about finding vulnerabilities; it&#39;s about shaping the future of secure AI by embedding an attacker&#39;s mindset into everything we build.</p>\n<p>You&#39;ll work at the intersection of offensive security, AI safety, and product development, collaborating with cross-functional teams to harden our systems against evolving threats. Your expertise will directly influence how we design, deploy, and protect our most critical assets , ensuring our agents remain resilient, trustworthy, and ahead of adversaries.</p>\n<p>Key responsibilities include:</p>\n<ul>\n<li><p>Proactively hunting for vulnerabilities in the interactions between our agentic applications, cloud infrastructure, and foundational models, with a focus on realistic, high-impact attack vectors.</p>\n</li>\n<li><p>Designing and executing red and purple team exercises, simulating sophisticated adversarial scenarios to stress-test our defenses and refine our detection capabilities.</p>\n</li>\n<li><p>Partnering with defensive teams to translate offensive insights into actionable improvements, from detection engineering to incident response.</p>\n</li>\n<li><p>Conducting in-depth penetration testing across our product suite, including AI-driven workflows, custom infrastructure, and user-facing interfaces.</p>\n</li>\n<li><p>Building and automating offensive tooling to scale your impact, leveraging cutting-edge techniques to stay ahead of emerging threats.</p>\n</li>\n<li><p>Communicating findings with clarity and conviction, ensuring technical and non-technical stakeholders understand risks and prioritize mitigations effectively.</p>\n</li>\n<li><p>Shaping Mistral AI&#39;s security strategy by contributing attacker-informed perspectives to threat modeling, risk assessment, and architectural decisions.</p>\n</li>\n</ul>\n<p>We&#39;re looking for someone with 7+ years of offensive security experience, deep knowledge of AI/ML security risks, and hands-on experience assessing modern technology stacks. A builder&#39;s mindset, strong intuition for trust boundaries, and outstanding communication skills are also essential.</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_1d67d51e-39e","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Mistral AI","sameAs":"https://mistral.ai","logo":"https://logos.yubhub.co/mistral.ai.png"},"x-apply-url":"https://jobs.lever.co/mistral/2414ad08-5756-4875-afb5-04d26464b397","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["offensive security","AI/ML security risks","custom Kubernetes deployments","cloud-native architectures","CI/CD pipelines","GitHub security best practices","macOS/Linux internals","Python/React-based applications","data science toolchains","AI/ML infrastructure"],"x-skills-preferred":["background in AI, data science, or related fields","experience in high-growth startups or research-driven organizations","expertise in adjacent disciplines"],"datePosted":"2026-04-17T12:47:11.116Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Paris"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"offensive security, AI/ML security risks, custom Kubernetes deployments, cloud-native architectures, CI/CD pipelines, GitHub security best practices, macOS/Linux internals, Python/React-based applications, data science toolchains, AI/ML infrastructure, background in AI, data science, or related fields, experience in high-growth startups or research-driven organizations, expertise in adjacent disciplines"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_2bc207d0-89b"},"title":"Senior Machine Learning Engineer","description":"<p>We are seeking a Senior Machine Learning Research Engineer to join the Machine Learning Science (MLS) team, within the Computational Science department. The ideal candidate has a strong knowledge in designing and building deep learning (DL) pipelines, and expertise in creating reliable, scalable artificial intelligence/machine learning (AI/ML) systems in a cloud environment.</p>\n<p>The MLS team at Freenome develops DL models using massive-scale genomic data that presents significant challenges for current training paradigms. The Senior Machine Learning Research Engineer will primarily be responsible for developing and deploying the infrastructure needed to support development of such DL models: enabling distributed DL pipelines, optimising hardware utilisation for efficient training, and performing model optimisations.</p>\n<p>As part of an interdisciplinary R&amp;D team, they will work in close collaboration with machine learning scientists, computational biologists and software engineers to accelerate the development of state-of-the-art ML/AI models and help Freenome achieve its mission.</p>\n<p>Key responsibilities include:</p>\n<ul>\n<li>Implementing and refining DL pipelines on distributed computing platforms to enhance the speed and efficiency of DL operations, including model training, data handling, model management, and inference.</li>\n<li>Collaborating closely with ML scientists and software engineers to understand current challenges and requirements and ensure that the DL model development pipelines created are perfectly aligned with scientific goals and operational needs.</li>\n<li>Continuously monitoring, evaluating, and optimising DL model training pipelines for performance and scalability.</li>\n<li>Staying up to date with the latest advancements in AI, ML, and related technologies, and quickly learning and adapting new tools and frameworks, if necessary.</li>\n<li>Developing and maintaining robust and reproducible DL pipelines that guarantee that DL pipelines can be reliably executed, maintaining consistency and accuracy of results.</li>\n<li>Driving performance improvements across our stack through profiling, optimisation, and benchmarking. Implementing efficient caching solutions and debugging distributed systems to accelerate both training and evaluation pipelines.</li>\n<li>Acting as a bridge facilitating communication between the engineering and scientific teams, documenting and sharing best practices to foster a culture of learning and continuous improvement.</li>\n</ul>\n<p>Must-haves include:</p>\n<ul>\n<li>MS or equivalent experience in a relevant, quantitative field such as Computer Science, Statistics, Mathematics, Software Engineering, with an emphasis on AI/ML theory and/or practical development.</li>\n<li>5+ years of post-MS industry experience working on developing AI/ML software engineering pipelines.</li>\n<li>Proficiency in a general-purpose programming language: Python (preferred), Java, Julia, C, C++, etc.</li>\n<li>Strong knowledge of ML and DL fundamentals and hands-on experience with machine learning frameworks such as PyTorch, TensorFlow, Jax or Scikit-learn.</li>\n<li>In-depth knowledge of scalable and distributed computing platforms that support complex model training (such as Ray or DeepSpeed) and their integration with ML developer tools like TensorBoard, Wandb, or MLflow.</li>\n<li>Experience with cloud platforms (e.g., AWS, Google Cloud, Azure) and how to deploy and manage AI/ML models and pipelines in a cloud environment.</li>\n<li>Understanding of containerisation technologies (e.g., Docker) and computing resource orchestration tools (e.g., Kubernetes) for deploying scalable ML/AI solutions.</li>\n<li>Proven track record of developing and optimising workflows for training DL models, large language models (LLMs), or similar for problems with high data complexity and volume.</li>\n<li>Experience managing large datasets, including data storage (such as HDFS or Parquet on S3), retrieval, and efficient data processing techniques (via libraries and executors such as PyArrow and Spark).</li>\n<li>Proficiency in version control systems (e.g., Git) and continuous integration/continuous deployment (CI/CD) practices to maintain code quality and automate development workflows.</li>\n<li>Expertise in building and launching large-scale ML frameworks in a scientific environment that supports the needs of a research team.</li>\n<li>Excellent ability to work effectively with cross-functional teams and communicate across disciplines.</li>\n</ul>\n<p>Nice-to-haves include:</p>\n<ul>\n<li>Experience working with large-scale genomics or biological datasets.</li>\n<li>Experience managing multimodal datasets, such as combinations of sequence, text, image, and other data.</li>\n<li>Experience GPU/Accelerator programming and kernel development (such as CUDA, Triton or XLA).</li>\n<li>Experience with infrastructure-as-code and configuration management.</li>\n<li>Experience cultivating MLOps and ML infrastructure best practices, especially around reliability, provisioning and monitoring.</li>\n<li>Strong track record of contributions to relevant DL projects, e.g. on github.</li>\n</ul>\n<p>The US target range of our base salary for new hires is $161,925 - $227,325. You will also be eligible to receive equity, cash bonuses, and a full range of medical, financial, and other benefits depending on the position offered.</p>\n<p>Freenome is proud to be an equal-opportunity employer, and we value diversity. Freenome does not discriminate on the basis of race, colour, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, veteran status, or any other status protected under federal, state, or local law.</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_2bc207d0-89b","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Freenome","sameAs":"https://freenome.com/","logo":"https://logos.yubhub.co/freenome.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/freenome/jobs/8013673002","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$161,925 - $227,325","x-skills-required":["Python","Java","Julia","C","C++","PyTorch","TensorFlow","Jax","Scikit-learn","Ray","DeepSpeed","TensorBoard","Wandb","MLflow","AWS","Google Cloud","Azure","Docker","Kubernetes","Git","Continuous Integration/Continuous Deployment"],"x-skills-preferred":["Large-scale genomics or biological datasets","Multimodal datasets","GPU/Accelerator programming and kernel development","Infrastructure-as-code and configuration management","MLOps and ML infrastructure best practices"],"datePosted":"2026-04-17T12:35:01.240Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Brisbane, California"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, Java, Julia, C, C++, PyTorch, TensorFlow, Jax, Scikit-learn, Ray, DeepSpeed, TensorBoard, Wandb, MLflow, AWS, Google Cloud, Azure, Docker, Kubernetes, Git, Continuous Integration/Continuous Deployment, Large-scale genomics or biological datasets, Multimodal datasets, GPU/Accelerator programming and kernel development, Infrastructure-as-code and configuration management, MLOps and ML infrastructure best practices","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":161925,"maxValue":227325,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_8e582153-6af"},"title":"Senior DevOps Lead - Cloud & Autonomous System","description":"<p>About Cyngn</p>\n<p>Cyngn is a publicly-traded autonomous technology company that deploys self-driving industrial vehicles to factories, warehouses, and other facilities throughout North America.</p>\n<p>We are a small company with under 100 employees, operating with the energy of a startup. However, we&#39;re also publicly traded, which means our employees get access to the liquidity of our publicly-traded equity.</p>\n<p>As a Senior DevOps Lead at Cyngn, you will play a vital role in architecting and managing infrastructure across cloud and autonomous vehicle systems. This position combines traditional cloud DevOps leadership with specialized expertise in robotics and autonomous systems infrastructure.</p>\n<p>Responsibilities</p>\n<ul>\n<li>Lead and architect cloud and vehicle infrastructure initiatives across AWS and ROS/Linux environments</li>\n<li>Design and implement scalable solutions for both cloud services and autonomous vehicle systems</li>\n<li>Establish and maintain DevOps best practices, CI/CD pipelines, and infrastructure as code</li>\n<li>Drive observability, monitoring, and incident response strategies</li>\n<li>Optimize performance and cost efficiency of cloud and edge computing resources</li>\n<li>Mentor team members and foster a developer-friendly environment</li>\n<li>Manage on-call rotations and incident response processes</li>\n<li>Architect solutions for processing and storing large-scale vehicle telemetry data</li>\n<li>Lead security initiatives and compliance efforts across infrastructure</li>\n</ul>\n<p>Requirements</p>\n<ul>\n<li>10+ years of relevant DevOps/Infrastructure experience</li>\n<li>Proven track record as a technical lead in platform or infrastructure teams</li>\n<li>Advanced expertise in AWS services, infrastructure as code (Terraform), and Kubernetes</li>\n<li>Strong experience with service mesh (Istio) and Helm/Kustomize</li>\n<li>Deep understanding of ROS/ROS2 and Linux kernel configurations</li>\n<li>Experience with GPU configurations and ML infrastructure</li>\n<li>Expertise in ARM and NVIDIA CUDA platform configurations</li>\n<li>Strong programming skills in Python and shell scripting</li>\n<li>Experience with infrastructure automation (Ansible)</li>\n<li>Expertise in CI/CD tools (Jenkins, GitHub Actions)</li>\n<li>Strong system architecture and design skills</li>\n<li>Excellence in technical documentation</li>\n<li>Outstanding problem-solving abilities</li>\n<li>Strong leadership and mentoring capabilities</li>\n</ul>\n<p>Nice to haves</p>\n<ul>\n<li>Experience with autonomous vehicle systems</li>\n<li>Track record of optimizing GPU-based ML infrastructure</li>\n<li>Experience with large-scale IoT deployments</li>\n<li>Contributions to open-source projects</li>\n<li>Experience with real-time systems and low-latency requirements</li>\n<li>Expertise in security implementations including SSO, IdP, and AWS Cognito</li>\n<li>Experience with JFrog artifactory and container registry management</li>\n<li>Proficiency in AWS IoT Greengrass</li>\n<li>Experience with container resource management on edge devices</li>\n<li>Understanding of CPU affinity and priority scheduling</li>\n<li>Track record of implementing cost optimization strategies</li>\n<li>Experience with scaling systems both horizontally and vertically</li>\n</ul>\n<p>Benefits &amp; Perks</p>\n<ul>\n<li>Health benefits (Medical, Dental, Vision, HSA and FSA (Health &amp; Dependent Daycare), Employee Assistance Program, 1:1 Health Concierge)</li>\n<li>Life, Short-term, and long-term disability insurance (Cyngn funds 100% of premiums)</li>\n<li>Company 401(k)</li>\n<li>Commuter Benefits</li>\n<li>Flexible vacation policy</li>\n<li>Sabbatical leave opportunity after five years with the company</li>\n<li>Paid Parental Leave</li>\n<li>Daily lunches for in-office employees</li>\n<li>Monthly meal and tech allowances for remote employees</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_8e582153-6af","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Cyngn","sameAs":"https://www.cyngn.com/","logo":"https://logos.yubhub.co/cyngn.com.png"},"x-apply-url":"https://jobs.lever.co/cyngn/1c31b7d8-cf85-472f-9358-1e10189cf815","x-work-arrangement":"remote","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$198,000-225,000 per year","x-skills-required":["AWS services","infrastructure as code (Terraform)","Kubernetes","service mesh (Istio)","Helm/Kustomize","ROS/ROS2","Linux kernel configurations","GPU configurations","ML infrastructure","ARM","NVIDIA CUDA platform configurations","Python","shell scripting","infrastructure automation (Ansible)","CI/CD tools (Jenkins, GitHub Actions)","system architecture and design skills","technical documentation","problem-solving abilities","leadership and mentoring capabilities"],"x-skills-preferred":["autonomous vehicle systems","optimizing GPU-based ML infrastructure","large-scale IoT deployments","open-source projects","real-time systems and low-latency requirements","security implementations including SSO, IdP, and AWS Cognito","JFrog artifactory and container registry management","AWS IoT Greengrass","container resource management on edge devices","CPU affinity and priority scheduling","cost optimization strategies","scaling systems both horizontally and vertically"],"datePosted":"2026-04-17T12:27:09.593Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Mountain View"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"AWS services, infrastructure as code (Terraform), Kubernetes, service mesh (Istio), Helm/Kustomize, ROS/ROS2, Linux kernel configurations, GPU configurations, ML infrastructure, ARM, NVIDIA CUDA platform configurations, Python, shell scripting, infrastructure automation (Ansible), CI/CD tools (Jenkins, GitHub Actions), system architecture and design skills, technical documentation, problem-solving abilities, leadership and mentoring capabilities, autonomous vehicle systems, optimizing GPU-based ML infrastructure, large-scale IoT deployments, open-source projects, real-time systems and low-latency requirements, security implementations including SSO, IdP, and AWS Cognito, JFrog artifactory and container registry management, AWS IoT Greengrass, container resource management on edge devices, CPU affinity and priority scheduling, cost optimization strategies, scaling systems both horizontally and vertically","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":198000,"maxValue":225000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_290c3d28-4b2"},"title":"Partner Solution Architect - ASEAN","description":"<p>About Mistral AI</p>\n<p>At Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life.</p>\n<p>We are a global company with teams distributed between France, USA, UK, Germany and Singapore. We are a diverse workforce that thrives in competitive environments and is committed to driving innovation.</p>\n<p>Why This Role Matters</p>\n<p>You will be the technical linchpin between Mistral and our strategic partners in ASEAN (Nvidia, Dell, Hyperscalers, Global System Integrators), translating our open-weight models and sovereign AI architecture into deployable, scalable solutions.</p>\n<p>By designing joint architectures, influencing partner GTM motions, and earning a seat at the CIO/CTO table, you will accelerate Mistral’s technical credibility and deployment velocity across Asia Pacific.</p>\n<p>This is a foundational role where you will define how open-weight AI is operationalized at scale in the region.</p>\n<p>What You Will Do</p>\n<p><strong>Partner Technical Leadership &amp; Architecture Design</strong></p>\n<ul>\n<li>Lead the technical design, deployment, and enablement of Mistral’s partner solutions, bridging our AI models with partner infrastructure (Nvidia, Dell, Hyperscalers, GSIs) to deliver scalable AI Labs, AI Factories, and sovereign AI architectures.</li>\n</ul>\n<ul>\n<li>Serve as the trusted technical advisor to partner CTOs, CIOs, and engineering leaders—shaping joint architectures, guiding GPU/model deployment strategies, and accelerating GTM execution.</li>\n</ul>\n<ul>\n<li>Design reference architectures and deployment patterns for partner-led implementations (e.g., multi-GPU inference clusters, AI Lab topologies, private AI clouds).</li>\n</ul>\n<ul>\n<li>Innovate the Executive Briefing Center (EBC) function for technical leaders (CIOs, CTOs, CDOs), positioning Mistral as the default choice for enterprise AI.</li>\n</ul>\n<ul>\n<li>Co-design sovereign AI reference architectures with Nvidia and Dell (H100, H200, GB200 platforms).</li>\n</ul>\n<p><strong>Co-Sell &amp; Revenue Enablement</strong></p>\n<ul>\n<li>Collaborate with Mistral’s partner and sales teams to progress deals, providing technical expertise to penetrate accounts and influence GTM pipeline.</li>\n</ul>\n<ul>\n<li>Support partners in qualifying/disqualifying opportunities, ensuring Mistral solutions unlock maximum value for customers.</li>\n</ul>\n<ul>\n<li>Deploy Mistral’s enterprise AI suite (models, fine-tuning, use-case building) in partner-led environments, tailoring solutions to customer requirements.</li>\n</ul>\n<p><strong>Trusted Advisor &amp; Lighthouse Implementations</strong></p>\n<ul>\n<li>Drive strategic partner-led opportunities through technical discovery, architecture design, and POC execution.</li>\n</ul>\n<ul>\n<li>Lead lighthouse deployments that become referenceable case studies (e.g., Singtel AI Grid, Accenture AI Lab).</li>\n</ul>\n<ul>\n<li>Establish a scalable partner enablement framework, training 100+ partner engineers across ASEAN.</li>\n</ul>\n<p><strong>Product Feedback &amp; Internal Collaboration</strong></p>\n<ul>\n<li>Coordinate with Mistral’s product and engineering teams to relay partner-specific requirements and feedback.</li>\n</ul>\n<ul>\n<li>Align joint GTM and technical execution between Mistral Science, Partner Engineering, and partner field teams.</li>\n</ul>\n<p>About You</p>\n<p><strong>Must-Have</strong></p>\n<ul>\n<li>10–15 years’ experience in partner-facing technical sales or solution architecture (e.g., Partner SA, Alliance Architect, Partner Technology Strategist).</li>\n</ul>\n<ul>\n<li>Proven ability to engage C-suite and senior technical stakeholders (CTO, CIO, Chief Architect) in strategic architecture discussions.</li>\n</ul>\n<ul>\n<li>Deep GenAI/LLM expertise: RAG, fine-tuning, prompt engineering, model evaluation, and deployment patterns.</li>\n</ul>\n<ul>\n<li>Technical mastery of AI/ML infrastructure (GPU clusters, cloud platforms, model deployment frameworks).</li>\n</ul>\n<ul>\n<li>Track record of co-designing/deploying joint solutions with ecosystem partners (Nvidia, Dell, AWS, Accenture, etc.).</li>\n</ul>\n<ul>\n<li>Executive communication: Ability to articulate science-driven value propositions to technical and business audiences.</li>\n</ul>\n<ul>\n<li>Entrepreneurial mindset: Operates autonomously in high-growth environments; creates playbooks, not follows them.</li>\n</ul>\n<ul>\n<li>Fluent in English; confident working across diverse, cross-cultural teams in Asia.</li>\n</ul>\n<p><strong>Nice-to-Have</strong></p>\n<ul>\n<li>Experience with open-weight LLMs or open-source AI stacks (Mistral, Hugging Face, LangChain, vLLM, RAG frameworks).</li>\n</ul>\n<ul>\n<li>Prior involvement in AI Lab, AI Factory, or Sovereign Cloud deployments.</li>\n</ul>\n<ul>\n<li>Familiarity with data governance, model evaluation, and GPU sizing for large-scale inference.</li>\n</ul>\n<ul>\n<li>Network across GSIs and infrastructure partners in Asia</li>\n</ul>\n<ul>\n<li>Exposure to multi-region partner programs or joint GTM initiatives in APJ.</li>\n</ul>\n<ul>\n<li>Bonus languages: Korean, Japanese, or Mandarin for regional partner engagement.</li>\n</ul>\n<p>What we offer</p>\n<ul>\n<li>💰 Competitive cash salary and equity</li>\n</ul>\n<ul>\n<li>🚑 Health Insurance : Best in Class</li>\n</ul>\n<ul>\n<li>🥎 Sport : $90 for gym membership allowance</li>\n</ul>\n<ul>\n<li>🥕 Food : $200 monthly allowance for meals (solution might evolve as we grow bigger)</li>\n</ul>\n<ul>\n<li>🚴 Transportation : $120/month for public transport or Parking charges reimbursed</li>\n</ul>\n<ul>\n<li>🏝️ PTO: 18 per year</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_290c3d28-4b2","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Mistral AI","sameAs":"https://mistral.ai/careers"},"x-apply-url":"https://jobs.lever.co/mistral/fe3542b5-4f99-4d62-af6a-fbdfd13bf0e4","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["GenAI/LLM expertise","RAG","fine-tuning","prompt engineering","model evaluation","deployment patterns","AI/ML infrastructure","GPU clusters","cloud platforms","model deployment frameworks","co-designing/deploying joint solutions","ecosystem partners","Nvidia","Dell","AWS","Accenture"],"x-skills-preferred":["open-weight LLMs","open-source AI stacks","Mistral","Hugging Face","LangChain","vLLM","RAG frameworks","data governance","model evaluation","GPU sizing","large-scale inference","GSIs","infrastructure partners","multi-region partner programs","joint GTM initiatives","APJ","Korean","Japanese","Mandarin"],"datePosted":"2026-03-10T11:27:47.209Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Singapore"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"GenAI/LLM expertise, RAG, fine-tuning, prompt engineering, model evaluation, deployment patterns, AI/ML infrastructure, GPU clusters, cloud platforms, model deployment frameworks, co-designing/deploying joint solutions, ecosystem partners, Nvidia, Dell, AWS, Accenture, open-weight LLMs, open-source AI stacks, Mistral, Hugging Face, LangChain, vLLM, RAG frameworks, data governance, model evaluation, GPU sizing, large-scale inference, GSIs, infrastructure partners, multi-region partner programs, joint GTM initiatives, APJ, Korean, Japanese, Mandarin"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_92883449-bdc"},"title":"Account Executive","description":"<p><strong>About the Role</strong></p>\n<p>As an Account Executive, you&#39;ll own the full sales cycle and help build our go-to-market foundation. You&#39;ll be responsible for driving new business across multiple customer segments, building strategic relationships, and contributing to our overall sales strategy and processes.</p>\n<p><strong>What You&#39;ll Do</strong></p>\n<ul>\n<li>Own the complete sales cycle from prospecting to close, focusing on new business acquisition and quota attainment.</li>\n<li>Build and maintain a robust pipeline based on strong inbound interest for our product.</li>\n<li>Conduct outbound prospecting and cultivate strong relationships with startups and enterprises using our self-serve platform, supporting them to scale usage across their organization.</li>\n<li>Deliver compelling technical demonstrations and presentations to prospects ranging from individual developers, founders, and C-suite executives.</li>\n<li>Take a consultative approach to understand customer needs, identify pain points, and tailor solutions that demonstrate measurable business impact.</li>\n<li>Gather competitive intelligence and enterprise customer requirements to inform product development and go-to-market strategy.</li>\n<li>Develop relationships with key ecosystem partners, industry organizations, and channels to create systematic access to qualified prospects.</li>\n<li>Contribute to building repeatable sales processes, playbooks, and best practices as we scale the sales organization.</li>\n<li>Work closely with marketing, product, engineering, and customer success teams to optimize the customer journey and drive growth.</li>\n</ul>\n<p><strong>About You</strong></p>\n<ul>\n<li>5+ years of proven B2B sales success with demonstrated ability to meet/exceed quotas in a consultative selling environment.</li>\n<li>Track record closing $100K+ annual contracts and navigating complex, multi-stakeholder sales processes.</li>\n<li>Experience thriving in an early-stage company environment where you&#39;ve built processes, adapted quickly, and operated with limited resources.</li>\n<li>Ability to understand and communicate complex technical products to both technical and business audiences.</li>\n<li>Deep understanding of AI/ML landscape, including large language models, API architectures, and developer integration patterns commonly used in AI applications.</li>\n<li>Exceptional presentation and communication abilities across all organizational levels.</li>\n<li>Proficiency with CRM platforms and sales engagement tools.</li>\n<li>Entrepreneurial mindset with ability to work independently, prioritize effectively, and drive results with minimal oversight</li>\n</ul>\n<p><strong>Bonus Points</strong></p>\n<ul>\n<li>Experience selling developer tools, AI/ML infrastructure, or API-first products.</li>\n<li>Previous experience as a first sales hire or early sales team member.</li>\n<li>Track record of building sales processes from the ground up.</li>\n<li>Familiarity with PLG (Product-Led Growth) motions and technical evaluation processes</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_92883449-bdc","directApply":true,"hiringOrganization":{"@type":"Organization","name":"OpenRouter","sameAs":"https://jobs.ashbyhq.com","logo":"https://logos.yubhub.co/openrouter.com.png"},"x-apply-url":"https://jobs.ashbyhq.com/openrouter/22d85a56-5500-40a5-9913-c98558d77f41","x-work-arrangement":"Remote","x-experience-level":"executive","x-job-type":"Full time","x-salary-range":null,"x-skills-required":["B2B sales","consultative selling","CRM platforms","sales engagement tools","AI/ML landscape","large language models","API architectures","developer integration patterns"],"x-skills-preferred":["developer tools","AI/ML infrastructure","API-first products"],"datePosted":"2026-03-09T09:49:07.705Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Remote (US)"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Sales","industry":"Technology","skills":"B2B sales, consultative selling, CRM platforms, sales engagement tools, AI/ML landscape, large language models, API architectures, developer integration patterns, developer tools, AI/ML infrastructure, API-first products"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_1d0184f1-be6"},"title":"Security Engineer","description":"<p><strong>About the Role</strong></p>\n<p>We&#39;re hiring our first Security Engineer to own the process of safeguarding our systems, infrastructure, applications, and data. As the first security hire, you will build out our security operations and vulnerability management process for our AI gateway platform. You&#39;ll implement programs, run tooling, ship security fixes, and drive remediation across our stack. You’ll be responsible for all aspects of ensuring the security of our platform and users. This isn&#39;t a compliance paperwork role; it&#39;s a hands-on security position with direct impact on how we protect millions of API requests daily. You&#39;ll work closely with engineering and senior leadership to ship security improvements that actually matter.</p>\n<p><strong>What You&#39;ll Do</strong></p>\n<ul>\n<li>Deploy and operate vulnerability scanning across our cloud infrastructure. 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You will have free reign to develop your own approaches with the mission guidance being your only bounds. No one will be there to empower your efforts, you will create your own influence by building relationships at the site and diving in at all phases to deliver success.</p>\n<p>You must thrive operating with ambiguity and have a willingness to own project outcomes, knowing that the buck stops with you.</p>\n<p>In this role, it is imperative that you are as comfortable in boots on a job site working to solve productivity issues with a group of blue-collar trades as you are working across executives at development and contractor partners to optimise contract and commercial structures that incentivise delivery speed.</p>\n<p><strong>It&#39;s a bonus if you:</strong></p>\n<p>· Understand AI/ML infrastructure requirements, including high-density power and advanced cooling systems</p>\n<p>· Have had leadership positions (General Superintendent, Project Manager) within a GC or EPC on hyperscale data center projects or in self-performance of hyperscale data center dev</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_5398d4f1-2e3","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/5128936008","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["data center delivery","construction projects","infrastructure deployment","leadership","project management","data center design","construction","real estate","construction management","project coordination","stakeholder management","risk management","process improvement"],"x-skills-preferred":["AI/ML infrastructure requirements","high-density power","advanced cooling systems","hyperscale data center projects","GC or EPC"],"datePosted":"2026-03-08T13:54:50.964Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA | New York City, NY"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"data center delivery, construction projects, infrastructure deployment, leadership, project management, data center design, construction, real estate, construction management, project coordination, stakeholder management, risk management, process improvement, AI/ML infrastructure requirements, high-density power, advanced cooling systems, hyperscale data center projects, GC or EPC"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_dd79f871-8f1"},"title":"Technical Program Manager, Infrastructure","description":"<p><strong>About the Role</strong></p>\n<p>Anthropic&#39;s Infrastructure organisation is the engine that powers our mission. Every breakthrough in AI safety research and every interaction users have with Claude depends on the systems we build and operate: massive clusters for training frontier models, production infrastructure serving millions of users reliably, and developer platforms that help engineers move fast without breaking things.</p>\n<p>As a Technical Program Manager for Infrastructure, you&#39;ll work across multiple infrastructure domains to coordinate complex programs that have broad organisational impact. You&#39;ll be solving novel scaling challenges at the frontier of what&#39;s possible, all while maintaining the security and reliability our mission demands.</p>\n<p>This role is ideal for someone who thrives in ambiguity and believes their job is to make everyone around them more effective. You&#39;ll partner closely with engineering leadership to drive strategic initiatives while ensuring seamless coordination between research, engineering, and product teams.</p>\n<p><strong>What you&#39;ll do:</strong></p>\n<p><strong>Developer Productivity &amp; Tooling</strong></p>\n<ul>\n<li>Drive cross-functional programs to improve developer environments, CI/CD infrastructure, and release processes that enable rapid innovation while maintaining high security standards</li>\n</ul>\n<ul>\n<li>Coordinate large-scale migrations and platform modernization efforts across engineering teams</li>\n</ul>\n<ul>\n<li>Partner with teams to measure and improve developer productivity metrics, identifying bottlenecks and driving systematic improvements</li>\n</ul>\n<ul>\n<li>Lead initiatives to integrate AI tools into development workflows, helping Anthropic be at the forefront of AI-assisted research and engineering</li>\n</ul>\n<p><strong>Infrastructure Reliability &amp; Operations</strong></p>\n<ul>\n<li>Drive programs to establish and achieve reliability targets across training infrastructure and production services</li>\n</ul>\n<ul>\n<li>Coordinate incident response improvements, post-mortem processes, and on-call rotations that help teams operate effectively</li>\n</ul>\n<ul>\n<li>Establish metrics and dashboards to track infrastructure health, capacity utilisation, and operational excellence</li>\n</ul>\n<p><strong>Cross-functional Coordination</strong></p>\n<ul>\n<li>Serve as the critical bridge between infrastructure teams, research, and product, translating technical complexities into clear updates for a variety of audiences</li>\n</ul>\n<ul>\n<li>Consult with stakeholders to deeply understand infrastructure, data, and compute needs, identifying solutions to support frontier research and product development</li>\n</ul>\n<ul>\n<li>Drive alignment on priorities and timelines across teams with competing constraints</li>\n</ul>\n<p><strong>You May Be a Good Fit If You</strong></p>\n<ul>\n<li>Have 5+ years of technical program management experience, with a track record of successfully delivering complex infrastructure programs in ML/AI systems or large-scale distributed systems</li>\n</ul>\n<ul>\n<li>Have deep technical understanding of infrastructure systems—enough to engage substantively with engineers, identify technical risks, and add value beyond project tracking</li>\n</ul>\n<ul>\n<li>Excel at creating structure and processes in ambiguous environments, bringing clarity to complex cross-team initiatives</li>\n</ul>\n<ul>\n<li>Have strong stakeholder management skills and can build trust with both technical and non-technical partners</li>\n</ul>\n<ul>\n<li>Are comfortable navigating competing priorities and using data to drive technical decisions</li>\n</ul>\n<ul>\n<li>Have experience with developer productivity initiatives, CI/CD systems, or infrastructure scaling</li>\n</ul>\n<ul>\n<li>Thrive in fast-paced environments and can balance strategic planning with tactical execution</li>\n</ul>\n<ul>\n<li>Are obsessed with reliability, scalability, security, and continuous improvement</li>\n</ul>\n<ul>\n<li>Have a passion for supporting internal partners like research to understand their unique needs</li>\n</ul>\n<ul>\n<li>Are passionate about AI infrastructure and understand the unique challenges of building and operating systems at frontier scale</li>\n</ul>\n<ul>\n<li>Experience with Kubernetes, cloud platforms (AWS, GCP, Azure), and ML infrastructure (GPU/TPU/Trainium clusters)</li>\n</ul>\n<ul>\n<li>Background working with research teams and translating their needs into concrete technical requirements</li>\n</ul>\n<ul>\n<li>Experience driving adoption of AI tools to improve engineering productivity</li>\n</ul>\n<ul>\n<li>Familiarity with observability tooling and practices</li>\n</ul>\n<p><strong>Deadline to Apply:</strong></p>\n<p>None, applications will be received on a rolling basis.</p>\n<p><strong>Logistics</strong></p>\n<p><strong>Education requirements:</strong></p>\n<p>We require at least a Bachelor&#39;s degree in a related field or equivalent experience.</p>\n<p><strong>Location-based hybrid policy:</strong></p>\n<p>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></p>\n<p>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></p>\n<p>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.</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_dd79f871-8f1","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/5111783008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$290,000 - $365,000 USD","x-skills-required":["Technical Program Management","Infrastructure","ML/AI systems","Distributed systems","Kubernetes","Cloud platforms","ML infrastructure"],"x-skills-preferred":["Developer productivity initiatives","CI/CD systems","Infrastructure scaling","Observability tooling and practices"],"datePosted":"2026-03-08T13:49:30.383Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA | New York City, NY | Seattle, WA"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Technical Program Management, Infrastructure, ML/AI systems, Distributed systems, Kubernetes, Cloud platforms, ML infrastructure, Developer productivity initiatives, CI/CD systems, Infrastructure scaling, Observability tooling and practices","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":290000,"maxValue":365000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_fb4fa003-a73"},"title":"Platform Hardware Security Engineer","description":"<p><strong>About the Role</strong></p>\n<p>We&#39;re seeking a Platform Hardware Security Engineer to design and implement security architectures for bare-metal infrastructure. You&#39;ll work with teams across Anthropic to build firmware, bootloaders, operating systems, and attestation systems to ensure the integrity of our infrastructure from the ground up.</p>\n<p>This role requires expertise in low-level systems security and the ability to architect solutions that balance security requirements with the performance demands of training AI models across our massive fleet.</p>\n<p><strong>What you&#39;ll do:</strong></p>\n<ul>\n<li>Design and implement secure boot chains from firmware through OS initialization for diverse hardware platforms (CPUs, BMCs, switches, peripherals, and embedded microcontrollers)</li>\n<li>Architect attestation systems that provide cryptographic proof of system state from hardware root of trust through application layer</li>\n<li>Develop measured boot implementations and runtime integrity monitoring</li>\n<li>Create reference architectures and security requirements for bare-metal deployments</li>\n<li>Integrate security controls with infrastructure teams without impacting training performance</li>\n<li>Prototype and validate security mechanisms before production deployment</li>\n<li>Conduct firmware vulnerability assessments and penetration testing</li>\n<li>Build firmware analysis pipelines for continuous security monitoring</li>\n<li>Document security architectures and maintain threat models</li>\n<li>Collaborate with software and hardware vendors to ensure security capabilities meet our requirements</li>\n</ul>\n<p><strong>Who you are:</strong></p>\n<ul>\n<li>8+ years of experience in systems security, with at least 5 years focused on firmware and hardware security (firmware, bootloaders, and OS-level security)</li>\n<li>Hands-on experience with secure boot, measured boot, and attestation technologies (TPM, Intel TXT, AMD SEV, ARM TrustZone)</li>\n<li>Strong understanding of cryptographic protocols and hardware security modules</li>\n<li>Experience with UEFI/BIOS or embedded firmware security, bootloader hardening, and chain of trust implementation</li>\n<li>Proficiency in low-level programming (C, Rust, Assembly) and systems programming</li>\n<li>Knowledge of firmware vulnerability assessment and threat modeling</li>\n<li>Track record of designing security architectures for complex, distributed systems</li>\n<li>Experience with supply chain security</li>\n<li>Ability to work effectively across hardware and software boundaries</li>\n<li>Knowledge of NIST firmware security guidelines and hardware security frameworks</li>\n</ul>\n<p><strong>Strong candidates may also have:</strong></p>\n<ul>\n<li>Experience with confidential computing technologies and hardware-based TEEs</li>\n<li>Knowledge of SLSA framework and software supply chain security standards</li>\n<li>Experience securing large-scale HPC or cloud infrastructure</li>\n<li>Contributions to open-source security projects (coreboot, CHIPSEC, etc.)</li>\n<li>Background in formal verification or security proof techniques</li>\n<li>Experience with silicon root of trust implementations</li>\n<li>Experience working with building foundational technical designs, operational leadership, and vendor collaboration</li>\n<li>Previous work with AI/ML infrastructure security</li>\n</ul>\n<p><strong>Logistics</strong></p>\n<ul>\n<li>Education requirements: We require at least a Bachelor&#39;s degree in a related field or equivalent experience.</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><strong>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.</strong></p>\n<p><strong>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.</strong></p>\n<p><strong>How we&#39;re different</strong></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.</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_fb4fa003-a73","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/4929689008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$405,000 - $485,000 USD","x-skills-required":["firmware security","hardware security","secure boot","measured boot","attestation technologies","cryptographic protocols","hardware security modules","UEFI/BIOS","embedded firmware security","bootloader hardening","chain of trust implementation","low-level programming","systems programming","firmware vulnerability assessment","threat modeling","supply chain security","NIST firmware security guidelines","hardware security frameworks"],"x-skills-preferred":["confidential computing technologies","hardware-based TEEs","SLSA framework","software supply chain security standards","large-scale HPC or cloud infrastructure","open-source security projects","formal verification","security proof techniques","silicon root of trust implementations","AI/ML infrastructure security"],"datePosted":"2026-03-08T13:47:08.377Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"New York City, NY; Seattle, WA; San Francisco, CA; Washington, DC"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"firmware security, hardware security, secure boot, measured boot, attestation technologies, cryptographic protocols, hardware security modules, UEFI/BIOS, embedded firmware security, bootloader hardening, chain of trust implementation, low-level programming, systems programming, firmware vulnerability assessment, threat modeling, supply chain security, NIST firmware security guidelines, hardware security frameworks, confidential computing technologies, hardware-based TEEs, SLSA framework, software supply chain security standards, large-scale HPC or cloud infrastructure, open-source security projects, formal verification, security proof techniques, silicon root of trust implementations, AI/ML infrastructure security","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":405000,"maxValue":485000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_b376a3b3-b21"},"title":"Machine Learning Systems Engineer, Research Tools","description":"<p><strong>About the Role:</strong></p>\n<p>We are seeking an experienced Machine Learning Systems Engineer to join our Encodings and Tokenization team at Anthropic. This cross-functional role will be instrumental in developing and optimising the encodings and tokenization systems used throughout our Finetuning workflows. As a bridge between our Pretraining and Finetuning teams, you&#39;ll build critical infrastructure that directly impacts how our models learn from and interpret data. Your work will be foundational to Anthropic&#39;s research progress, enabling more efficient and effective training of our AI systems while ensuring they remain reliable, interpretable, and steerable.</p>\n<p><strong>Responsibilities:</strong></p>\n<ul>\n<li>Design, develop, and maintain tokenization systems used across Pretraining and Finetuning workflows</li>\n<li>Optimise encoding techniques to improve model training efficiency and performance</li>\n<li>Collaborate closely with research teams to understand their evolving needs around data representation</li>\n<li>Build infrastructure that enables researchers to experiment with novel tokenization approaches</li>\n<li>Implement systems for monitoring and debugging tokenization-related issues in the model training pipeline</li>\n<li>Create robust testing frameworks to validate tokenization systems across diverse languages and data types</li>\n<li>Identify and address bottlenecks in data processing pipelines related to tokenization</li>\n<li>Document systems thoroughly and communicate technical decisions clearly to stakeholders across teams</li>\n</ul>\n<p><strong>You May Be a Good Fit If You:</strong></p>\n<ul>\n<li>Have significant software engineering experience with demonstrated machine learning expertise</li>\n<li>Are comfortable navigating ambiguity and developing solutions in rapidly evolving research environments</li>\n<li>Can work independently while maintaining strong collaboration with cross-functional teams</li>\n<li>Are results-oriented, with a bias towards flexibility and impact</li>\n<li>Have experience with machine learning systems, data pipelines, or ML infrastructure</li>\n<li>Are proficient in Python and familiar with modern ML development practices</li>\n<li>Have strong analytical skills and can evaluate the impact of engineering changes on research outcomes</li>\n<li>Pick up slack, even if it goes outside your job description</li>\n<li>Enjoy pair programming (we love to pair!)</li>\n<li>Care about the societal impacts of your work and are committed to developing AI responsibly</li>\n</ul>\n<p><strong>Strong Candidates May Also Have Experience With:</strong></p>\n<ul>\n<li>Working with machine learning data processing pipelines</li>\n<li>Building or optimising data encodings for ML applications</li>\n<li>Implementing or working with BPE, WordPiece, or other tokenization algorithms</li>\n<li>Performance optimisation of ML data processing systems</li>\n<li>Multi-language tokenisation challenges and solutions</li>\n<li>Research environments where engineering directly enables scientific progress</li>\n<li>Distributed systems and parallel computing for ML workflows</li>\n<li>Large language models or other transformer-based architectures (not required)</li>\n</ul>\n<p><strong>Logistics</strong></p>\n<ul>\n<li>Education requirements: We require at least a Bachelor&#39;s degree in a related field or equivalent experience.</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><strong>How we&#39;re different</strong></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.</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_b376a3b3-b21","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/4952079008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$320,000 - $405,000 USD","x-skills-required":["Machine Learning","Software Engineering","Python","Data Pipelines","ML Infrastructure","Tokenization","Encoding","BPE","WordPiece"],"x-skills-preferred":["Distributed Systems","Parallel Computing","Large Language Models","Transformer-Based Architectures"],"datePosted":"2026-03-08T13:44:14.348Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA | New York City, NY | Seattle, WA"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Machine Learning, Software Engineering, Python, Data Pipelines, ML Infrastructure, Tokenization, Encoding, BPE, WordPiece, Distributed Systems, Parallel Computing, Large Language Models, Transformer-Based Architectures","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":320000,"maxValue":405000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_d4cc9e89-c94"},"title":"Infrastructure Engineer, Sandboxing","description":"<p><strong>About Anthropic</strong></p>\n<p>Anthropic&#39;s mission is to create reliable, interpretable, and steerable AI systems. 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 is seeking an experienced Infrastructure Engineer to join our Sandboxing team within the Research organisation. In this role, you&#39;ll build and scale the systems that enable researchers to safely execute and experiment with AI-generated code and interactions in isolated environments.</p>\n<p>As our models become more capable, the infrastructure supporting secure execution environments becomes increasingly critical. You&#39;ll work on distributed systems that must operate reliably at significant scale while maintaining strong security boundaries. Your work will directly support Anthropic&#39;s mission to develop AI systems that are safe, beneficial, and trustworthy.</p>\n<p><strong>Responsibilities</strong></p>\n<ul>\n<li>Design, build, and operate distributed backend systems that power secure sandboxed execution environments</li>\n<li>Scale infrastructure to meet growing research and product demands while maintaining reliability and performance</li>\n<li>Implement and maintain serverless architectures and container orchestration systems</li>\n<li>Collaborate with research teams to understand requirements and translate them into robust infrastructure solutions</li>\n<li>Develop monitoring, alerting, and observability systems to ensure operational excellence</li>\n<li>Participate in on-call rotations and incident response to maintain system reliability</li>\n<li>Contribute to infrastructure automation and tooling that improves developer productivity</li>\n<li>Partner with security teams to ensure sandboxing infrastructure maintains appropriate isolation guarantees</li>\n</ul>\n<p><strong>You may be a good fit if you</strong></p>\n<ul>\n<li>Have 5+ years of experience building and operating backend infrastructure at scale</li>\n<li>Have deep expertise in distributed systems design and implementation</li>\n<li>Have strong operational experience, including debugging complex production issues</li>\n<li>Are proficient with cloud platforms, particularly GCP/GCS (experience with AWS or Azure is also valuable)</li>\n<li>Have experience with containerization technologies (Docker, Kubernetes) and understand their security implications</li>\n<li>Are comfortable working with infrastructure as code and modern DevOps practices</li>\n<li>Have strong programming skills in languages such as Python, Go, or Rust</li>\n<li>Are results-oriented with a bias towards flexibility and impact</li>\n<li>Care about the societal impacts of your work and are motivated by Anthropic&#39;s mission</li>\n</ul>\n<p><strong>Strong candidates may also have experience with</strong></p>\n<ul>\n<li>Serverless architectures and functions-as-a-service platforms (Cloud Functions, Cloud Run, Lambda)</li>\n<li>Designing and implementing secure multi-tenant systems</li>\n<li>High-performance computing environments or ML infrastructure</li>\n<li>Linux systems internals, including namespaces, cgroups, and seccomp</li>\n<li>Network security and isolation techniques</li>\n<li>Building systems that support research workflows and rapid iteration</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></p>\n<p>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></p>\n<p>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><strong>Your safety matters to us.</strong></p>\n<p>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><strong>How we&#39;re different</strong></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 everyone is aligned and working towards the same goals.</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_d4cc9e89-c94","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/5030680008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$300,000 - $405,000 USD","x-skills-required":["Distributed systems design and implementation","Cloud platforms (GCP/GCS, AWS, Azure)","Containerization technologies (Docker, Kubernetes)","Infrastructure as code and modern DevOps practices","Programming skills in languages such as Python, Go, or Rust"],"x-skills-preferred":["Serverless architectures and functions-as-a-service platforms","Secure multi-tenant systems","High-performance computing environments or ML infrastructure","Linux systems internals","Network security and isolation techniques"],"datePosted":"2026-03-08T13:43:40.209Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA | New York City, NY | Seattle, WA"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Distributed systems design and implementation, Cloud platforms (GCP/GCS, AWS, Azure), Containerization technologies (Docker, Kubernetes), Infrastructure as code and modern DevOps practices, Programming skills in languages such as Python, Go, or Rust, Serverless architectures and functions-as-a-service platforms, Secure multi-tenant systems, High-performance computing environments or ML infrastructure, Linux systems internals, Network security and isolation techniques","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_75ad55ca-61b"},"title":"Research Engineer / Research Scientist - Foundations Retrieval IC","description":"<p><strong>Job Posting</strong></p>\n<p><strong>Research Engineer / Research Scientist - Foundations Retrieval IC</strong></p>\n<p><strong>Location</strong></p>\n<p>San Francisco</p>\n<p><strong>Employment Type</strong></p>\n<p>Full time</p>\n<p><strong>Department</strong></p>\n<p>Research</p>\n<p><strong>Compensation</strong></p>\n<ul>\n<li>$445K – $555K • Offers Equity</li>\n</ul>\n<p>The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. 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Our goal is to advance the science and data that enable our training and scaling efforts, with a particular focus on future frontier models. Pushing the boundaries of data, scaling laws, optimization techniques, model architectures, and efficiency improvements to propel our science.</p>\n<p><strong>About the Role</strong></p>\n<p>We’re looking for a researcher focused on our embedding retrieval efforts. You’ll work with a team of world-class research scientists and engineers developing foundational technology that enables models to retrieve and condition on the right information, at the right time. This includes designing new embedding training objectives, scalable vector store architectures, and dynamic indexing methods.</p>\n<p>This work will support retrieval across many OpenAI products and internal research efforts, with opportunities for scientific publication and deep technical impact.</p>\n<p>This role is based in San Francisco, CA. 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That&#39;s why we&#39;re seeking a software engineer to help us build out our trust and safety capabilities.</p>\n<p>In this role, you&#39;ll work with our entire engineering team to design and implement systems that detect and prevent abuse, promote user safety, and reduce risk across our platform. You&#39;ll be at the forefront of our efforts to ensure that the immense potential of AI is harnessed in a responsible and sustainable manner.</p>\n<p><strong>In this role, you will:</strong></p>\n<ul>\n<li>Architect, build, and maintain anti-abuse and content moderation infrastructure designed to protect us and end users from unwanted behavior.</li>\n</ul>\n<ul>\n<li>Work closely with our other engineers and researchers to utilize both industry standard and novel AI techniques to measure, monitor and improve AI models’ alignment to human values.</li>\n</ul>\n<ul>\n<li>Diagnose and remediate active incidents on the platform and build new tooling and infrastructure that address the root causes of system failure.</li>\n</ul>\n<p><strong>You might thrive in this role if:</strong></p>\n<ul>\n<li>You have built and run production services in a high growth, rapidly scaling environment.</li>\n</ul>\n<ul>\n<li>You can debug live issues and restore systems quickly.</li>\n</ul>\n<ul>\n<li>You have worked on content safety, fraud, or abuse, or are motivated and excited to work on present-day (“now-term”) AI safety.</li>\n</ul>\n<ul>\n<li>You have experience with Python or with modern languages such as C++, Rust, or Go, and are able to quickly ramp up on Python.</li>\n</ul>\n<ul>\n<li>You understand the trade-offs of capabilities and risks and navigate them to deploy novel products and features safely.</li>\n</ul>\n<ul>\n<li>You can critically assess risks of a new product or feature and devise innovative solutions to mitigate these risks without harming the product experience.</li>\n</ul>\n<ul>\n<li>You’re pragmatic. 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You’ll work closely with product, infrastructure, security, and legal teams to embed privacy-by-design into our data and access layers.</p>\n<p>This is a hands-on, high-impact role for an experienced engineer who is passionate about protecting user data while enabling innovation.</p>\n<p><strong><strong>What You’ll Do</strong></strong></p>\n<ul>\n<li>Design, build, and operate backend services that enforce policy-driven data access, lifecycle controls, and privacy protections.</li>\n</ul>\n<ul>\n<li>Develop distributed authorization and identity-aware enforcement mechanisms integrated directly into data services and control planes.</li>\n</ul>\n<ul>\n<li>Implement auditability, policy hooks, and enforcement observability to ensure compliance is continuously verifiable.</li>\n</ul>\n<ul>\n<li>Partner with Security, Legal, and Compliance to convert privacy requirements into scalable technical designs and developer-friendly APIs.</li>\n</ul>\n<ul>\n<li>Harden data platforms and backend services through schema-level controls and data handling constraints by default.</li>\n</ul>\n<ul>\n<li>Collaborate with infrastructure teams to ensure consistent enforcement across systems while minimizing duplicated implementations.</li>\n</ul>\n<ul>\n<li>Contribute patterns, libraries, and education that elevate trustworthy data access patterns across the organization.</li>\n</ul>\n<p><strong><strong>You Might Thrive in This Role If You Have</strong></strong></p>\n<ul>\n<li><strong>5+ years of industry experience</strong> building and operating backend or infrastructure systems in production.</li>\n</ul>\n<ul>\n<li><strong>Strong software engineering fundamentals</strong>, with fluency in at least one major programming language (e.g., Python, Go, Rust, C++, Java).</li>\n</ul>\n<ul>\n<li>Experience with distributed authorization, RBAC/ACL systems, encryption-based access, or policy engines.</li>\n</ul>\n<ul>\n<li><strong>Familiarity with global privacy regulations</strong> and their architectural implications.</li>\n</ul>\n<ul>\n<li><strong>Ability to influence and collaborate</strong> with teams across legal, compliance, product, and engineering.</li>\n</ul>\n<ul>\n<li>A <strong>bias toward practical, impactful solutions</strong> that balance privacy protections with product needs.</li>\n</ul>\n<p><strong><strong>Nice to Have</strong></strong></p>\n<ul>\n<li>Experience with cloud platforms (e.g., Azure, AWS, GCP) and large-scale data systems.</li>\n</ul>\n<ul>\n<li>Background in security engineering, privacy engineering, or data governance.</li>\n</ul>\n<ul>\n<li>Experience with control-plane or metadata-driven enforcement systems.</li>\n</ul>\n<ul>\n<li>Exposure to data platforms or ML infrastructure.</li>\n</ul>\n<ul>\n<li>Prior experience in a regulated or highly sensitive data environment.</li>\n</ul>\n<p><strong>About OpenAI</strong></p>\n<p>OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.</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_ec06a431-7fa","directApply":true,"hiringOrganization":{"@type":"Organization","name":"OpenAI","sameAs":"https://jobs.ashbyhq.com","logo":"https://logos.yubhub.co/openai.com.png"},"x-apply-url":"https://jobs.ashbyhq.com/openai/23b158fe-709e-4bf5-856c-d10953d32f60","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$230K – $385K • Offers Equity","x-skills-required":["Python","Go","Rust","C++","Java","Distributed authorization","RBAC/ACL systems","Encryption-based access","Policy engines","Global privacy regulations","Cloud platforms","Large-scale data systems","Security engineering","Privacy engineering","Data governance","Control-plane or metadata-driven enforcement systems","Data platforms","ML infrastructure"],"x-skills-preferred":[],"datePosted":"2026-03-06T18:27:07.514Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, Seattle"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, Go, Rust, C++, Java, Distributed authorization, RBAC/ACL systems, Encryption-based access, Policy engines, Global privacy regulations, Cloud platforms, Large-scale data systems, Security engineering, Privacy engineering, Data governance, Control-plane or metadata-driven enforcement systems, Data platforms, ML infrastructure","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":230000,"maxValue":385000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_6f3679c9-766"},"title":"Software Engineer, Monetization Infrastructure","description":"<p><strong>Software Engineer, Monetization Infrastructure (SF/Seattle)</strong></p>\n<p><strong>Location</strong></p>\n<p>San Francisco</p>\n<p><strong>Employment Type</strong></p>\n<p>Full time</p>\n<p><strong>Department</strong></p>\n<p>Applied AI</p>\n<p><strong>Compensation</strong></p>\n<ul>\n<li>$230K – $385K • Offers Equity</li>\n</ul>\n<p>The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. 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Our mission is to develop user-first, privacy-preserving monetization products—including next-generation ads experiences—that strengthen user trust, unlock economic opportunity, and support OpenAI’s long-term innovation.</p>\n<p>Monetization plays a critical role in enabling OpenAI to continue pushing the boundaries of AI capabilities while ensuring the benefits of AGI are broadly shared. We believe monetization must be aligned with user value, uphold rigorous privacy and safety standards, and sustain a healthy ecosystem of developers and businesses.</p>\n<p>This team operates in a greenfield environment and moves quickly through prototyping, experimentation, and iterative deployment. We partner closely with Product, Design, and Research to bring research breakthroughs into real-world systems at global scale.</p>\n<p><strong>About the Role</strong></p>\n<p>We’re looking for an experienced Software Engineer to help build the core infrastructure behind OpenAI’s monetization and ads systems. In this foundational role, you’ll architect and implement distributed systems that power OpenAI’s monetization stack—focusing on reliability, performance, privacy, and large-scale operation.</p>\n<p>You’ll work across backend, systems, and platform layers to define and implement 0→1 infrastructure, partnering closely with Product, Design, and Research to shape the future of monetized AI experiences. Your work will enable both internal and external teams to build on safe, scalable, and robust monetization primitives.</p>\n<p>This role is exclusively based across our San Francisco &amp; Seattles sites. We offer relocation assistance to new employees.</p>\n<p><strong>In this role, you will:</strong></p>\n<ul>\n<li>Design and build the foundational backend and infrastructure powering OpenAI’s monetization and ads systems</li>\n</ul>\n<ul>\n<li>Architect large-scale distributed systems that meet strict requirements for reliability, privacy, security, and performance</li>\n</ul>\n<ul>\n<li>Develop APIs, infrastructure services, and internal platforms that support ads creation, delivery, measurement, and optimization</li>\n</ul>\n<ul>\n<li>Work closely with Product, Research, and Design to translate requirements into scalable technical solutions</li>\n</ul>\n<ul>\n<li>Drive 0→1 infra development through rapid prototyping, experimentation, and iterative improvements</li>\n</ul>\n<ul>\n<li>Contribute to the long-term technical strategy and roadmap for the monetization infra stack</li>\n</ul>\n<ul>\n<li>Ensure high engineering rigor through excellent testing, documentation, observability, and operational best practices</li>\n</ul>\n<ul>\n<li>Build for safety, privacy, fairness, and policy alignment from first principles</li>\n</ul>\n<ul>\n<li>Collaborate across engineering orgs to ensure the infra layer is flexible, performant, and resilient</li>\n</ul>\n<p><strong>You might thrive in this role if you:</strong></p>\n<ul>\n<li>Have 10+ years of experience building and operating large-scale distributed systems</li>\n</ul>\n<ul>\n<li>Have experience designing mission-critical systems with demanding reliability, performance, and correctness requirements</li>\n</ul>\n<ul>\n<li>Think in systems—architecture, data flows, operational concerns, observability, and long-term maintainability</li>\n</ul>\n<ul>\n<li>Are comfortable defining technical direction in ambiguous 0→1 environments</li>\n</ul>\n<ul>\n<li>Enjoy working cross-functionally to shape product requirements and system capabilities</li>\n</ul>\n<ul>\n<li>Communicate clearly, reason holistically, and make decisions grounded in user needs and long-term system health</li>\n</ul>\n<ul>\n<li>Bonus: Experience in ads systems, marketplaces, AI/ML infra, or other monetization-intensive domains</li>\n</ul>\n<p><strong>About OpenAI</strong></p>\n<p>OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through research and collaboration.</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_6f3679c9-766","directApply":true,"hiringOrganization":{"@type":"Organization","name":"OpenAI","sameAs":"https://jobs.ashbyhq.com","logo":"https://logos.yubhub.co/openai.com.png"},"x-apply-url":"https://jobs.ashbyhq.com/openai/a4ea79c8-e79f-4126-8c1f-032289024961","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$230K – $385K • Offers Equity","x-skills-required":["Software Engineer","Distributed Systems","APIs","Infrastructure Services","Internal Platforms","Ads Creation","Delivery","Measurement","Optimization","Backend","Systems","Platform Layers","0→1 Infrastructure","Reliability","Performance","Privacy","Security","Large-Scale Operation","Testing","Documentation","Observability","Operational Best Practices","Safety","Privacy","Fairness","Policy Alignment"],"x-skills-preferred":["Ads Systems","Marketplaces","AI/ML Infra","Monetization-Intensive Domains"],"datePosted":"2026-03-06T18:25:22.229Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Software Engineer, Distributed Systems, APIs, Infrastructure Services, Internal Platforms, Ads Creation, Delivery, Measurement, Optimization, Backend, Systems, Platform Layers, 0→1 Infrastructure, Reliability, Performance, Privacy, Security, Large-Scale Operation, Testing, Documentation, Observability, Operational Best Practices, Safety, Privacy, Fairness, Policy Alignment, Ads Systems, Marketplaces, AI/ML Infra, Monetization-Intensive Domains","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":230000,"maxValue":385000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_3f5ece56-eaa"},"title":"Senior Machine Learning Engineer, AI Platform - PhD Early Career","description":"<p><strong>[2026] Senior Machine Learning Engineer, AI Platform - PhD Early Career</strong></p>\n<p>San Mateo, CA, United States</p>\n<p>Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators.</p>\n<p>At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device.</p>\n<p>A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone.</p>\n<p><strong>You Will</strong></p>\n<p>As a Senior Machine Learning Engineer on the AI Platform team, you will be a key contributor to building the cutting-edge systems that power AI at Roblox. You will focus on one of three high-impact tracks:</p>\n<p><strong>Track 1: AI Platform Projects</strong></p>\n<ul>\n<li>Pioneer next-generation AI tooling to enhance the efficiency, cost, and usability of ML@Roblox.</li>\n<li>Build and maintain core platform components: Serving Layer, Model Registry, Pipeline Orchestrator, and Training/Inference control planes.</li>\n<li>Design great developer experiences (paved-road templates, tooling, visualizations) to reduce time-to-production and ensure foundational AI systems are scalable and reliable.</li>\n</ul>\n<p><strong>Track 2: Distributed Inference &amp; Systems Optimization</strong></p>\n<ul>\n<li>Architect and implement scalable distributed inference systems for efficiently serving LLMs and Large Recommender Models at massive scale.</li>\n<li>Conduct deep, low-level performance analysis and optimize ML models (using techniques like continuous batching, speculative decoding, and quantization) and systems on GPU architectures to maintain peak performance and stability.</li>\n</ul>\n<p><strong>Track 3: Information Retrieval &amp; RAG for Gen AI</strong></p>\n<ul>\n<li>Lead the design and development of Retrieval-Augmented Generation (RAG) systems.</li>\n<li>Build and maintain core information retrieval infrastructure—vector databases and knowledge graphs—to enable accurate grounding of Gen AI models.</li>\n<li>Ship language models and 3D objects as a service for the Roblox community, making creation easier.</li>\n</ul>\n<p><strong>You Have</strong></p>\n<ul>\n<li>Possessing or pursuing a Ph.D. in Computer Science, Computer Engineering, Mathematics, Statistics, or a related technical field, with a thesis aligned to Roblox’s research areas.</li>\n<li>Experience with high performance distributed systems, ML Infrastructure, LLM fine tuning/RL, Information Retrieval and Gen AI context generation.</li>\n<li>Expertise in one or more of the following key areas:</li>\n<li>AI/ML Platform Data stores - Features stores, Vector DBs and Knowledge Graphs.</li>\n<li>LLMs - Fine tuning, Safety.</li>\n<li>Agentic systems - Agent evaluation, context engineering.</li>\n</ul>\n<ul>\n<li>Experience building agentic applications with context for real world applications.</li>\n<li>Collaborative mindset and experience integrating and deploying optimized models with cross-functional teams, including data scientists and software engineers.</li>\n<li>Experience with graph databases and large-scale GNNs (Graph Neural Networks)</li>\n<li>Experience working with Kubernetes</li>\n<li>Experience working with one or more cloud providers (e.g., AWS, Azure, GCP)</li>\n<li>Experience working with high availability systems</li>\n<li>Experience working with ML models, LLMs or other AI systems</li>\n</ul>\n<p>You may redact age, date of birth, and dates of attendance/graduation from your resume if you prefer.</p>\n<p>As you apply, you can find more information about our process by signing up for Speak\\_. You&#39;ll gain access to our practice assessment, comprehensive guides, FAQs, and modules designed to help you ace the hiring process.</p>\n<p>For roles that are based at our headquarters in San Mateo, CA: The starting base pay for this position is as shown below. The actual base pay is dependent upon a variety of job-related factors such as professional background, training, work experience, location, business needs and market demand. Therefore, in some circumstances, the actual salary could fall outside of this expected range. This pay range is subject to change and may be modified in the future. All full-time employees are also eligible for equity compensation and for benefits as described on <strong>this page</strong>.</p>\n<p>Annual Salary Range</p>\n<p>$195,780—$242,100 USD</p>\n<p>Roles that are based in an office are onsite Tuesday, Wednesday, and Thursday, with optional presence on Monday and Friday (unless otherwise noted).</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_3f5ece56-eaa","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Roblox","sameAs":"https://careers.roblox.com","logo":"https://logos.yubhub.co/careers.roblox.com.png"},"x-apply-url":"https://careers.roblox.com/jobs/7403998","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$195,780—$242,100 USD","x-skills-required":["AI/ML Platform Data stores","LLMs","Agentic systems","Graph databases","Kubernetes","Cloud providers","High availability systems","ML models","LLMs","AI systems"],"x-skills-preferred":["Distributed systems","ML Infrastructure","RL","Information Retrieval","Gen AI context generation","Vector databases","Knowledge graphs"],"datePosted":"2026-03-06T14:19:52.481Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Mateo, CA"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"AI/ML Platform Data stores, LLMs, Agentic systems, Graph databases, Kubernetes, Cloud providers, High availability systems, ML models, LLMs, AI systems, Distributed systems, ML Infrastructure, RL, Information Retrieval, Gen AI context generation, Vector databases, Knowledge graphs","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":195780,"maxValue":242100,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_171cb453-957"},"title":"Technical Program Manager - Infrastructure","description":"<p><strong>Summary</strong></p>\n<p>Microsoft AI are looking for a talented Technical Program Manager to join their Infrastructure team in Mountain View. 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This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that&#39;s revolutionising AI technology. You&#39;ll work directly with leadership to shape the company&#39;s direction in the AI market.</p>\n<p><strong>About the Role</strong></p>\n<p>As a Technical Program Manager - Infrastructure, you will be responsible for coordinating projects and programs related to AI/ML infrastructure, including end-to-end planning, timelines, milestones, performance metrics, and resource needs. You will collaborate with product teams, engineers, researchers, and external partners to identify gaps and drive timelines toward resolution and mitigation. 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In this role, you&#39;ll lead efforts to build and maintain secure, scalable infrastructure that empowers engineers to innovate quickly and safely.</p>\n<p><strong>What you&#39;ll do</strong></p>\n<p>Partner with infrastructure and engineering teams to embed security into development workflows and promote secure-by-default patterns.</p>\n<ul>\n<li>Build Terraform modules with built-in security guardrails, such as logging, encryption, and automated threat detection enablement.</li>\n</ul>\n<ul>\n<li>Deploy cloud-native detection capabilities using AWS GuardDuty, Security Hub, and custom detection rules to identify credential compromise, crypto-mining, and lateral movement.</li>\n</ul>\n<p><strong>What you need</strong></p>\n<ul>\n<li>8+ years of experience in Cloud Infrastructure, Platform Engineering, or similar roles.</li>\n</ul>\n<ul>\n<li>Proven track record of building and scaling infrastructure at high-growth technology companies.</li>\n</ul>\n<ul>\n<li>Deep understanding of cloud-native architectures, microservices, and distributed systems.</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_49bcfb3f-03d","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Perplexity","sameAs":"https://jobs.ashbyhq.com","logo":"https://logos.yubhub.co/perplexity.com.png"},"x-apply-url":"https://jobs.ashbyhq.com/perplexity/b932d73f-49f3-4367-8fa7-a22f760e55a3","x-work-arrangement":"remote","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$220K – $405K","x-skills-required":["Cloud Infrastructure","Platform Engineering","Cloud-Native Architectures","Microservices","Distributed Systems"],"x-skills-preferred":["Python","Go","AI/ML Infrastructure","Multi-Cloud Environments"],"datePosted":"2026-03-04T12:27:52.028Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, London, New York City, Remote (United States), Serbia"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Cloud Infrastructure, Platform Engineering, Cloud-Native Architectures, Microservices, Distributed Systems, Python, Go, AI/ML Infrastructure, Multi-Cloud Environments","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":220000,"maxValue":405000,"unitText":"YEAR"}}}]}