{"version":"0.1","company":{"name":"YubHub","url":"https://yubhub.co","jobsUrl":"https://yubhub.co/jobs/skill/red-teaming"},"x-facet":{"type":"skill","slug":"red-teaming","display":"Red Teaming","count":15},"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_f77c41bb-0ad"},"title":"Application Security Engineer","description":"<p>We are seeking an experienced Application Security Engineer to join our team. As a subject matter expert, you will have direct experience in a wide range of security technologies, tools, and methodologies. The role is suited for an experienced Application Security engineer with proven understanding in enterprise security and AI security and will focus on building toolsets and processes to drive adoption of secure practices across the enterprise.</p>\n<p>The team fosters a collaborative environment and is building a best-in-class program to partner with the business to protect the Firm’s information and computer systems. Millennium is a complex and robust technical environment and securing the Firm from external and internal threats is a top priority.</p>\n<p><strong>Responsibilities</strong></p>\n<ul>\n<li>Define and implement security guardrails for Generative AI, LLMs, and Agentic frameworks, ensuring safe enterprise adoption.</li>\n<li>Conduct specialized threat modeling, red teaming, and risk assessments for AI/ML models (e.g., testing for prompt injection, model theft, and data poisoning).</li>\n<li>Lead risk management activities, including application risk assessments, design reviews, and mitigation strategies for IT projects.</li>\n<li>Engage throughout the SDLC to identify vulnerabilities, conduct code reviews/penetration testing, and enforce secure coding standards.</li>\n<li>Evangelize AppSec and AI security best practices through developer education, training materials, and outreach.</li>\n<li>Design robust security architectures and integrate automated security testing (SAST/DAST/SCA) into CI/CD pipelines.</li>\n<li>Partner with Technology, Trading, Legal, and Compliance to create policies and communicate technical risks to non-technical stakeholders.</li>\n</ul>\n<p><strong>Qualifications</strong></p>\n<ul>\n<li>Bachelor&#39;s degree or higher in Computer Science, Computer Engineering, IT Security or related field.</li>\n<li>5+ years’ experience working as an Application Security Engineer, Software Engineer, or similar role.</li>\n<li>Deep understanding of AI-specific risks (OWASP Top 10 for LLMs) and experience securing applications utilizing LLMs.</li>\n<li>Experience working with AI models, Agentic frameworks and security risks associated with AI.</li>\n<li>Experience in working with global teams, collaborating on code and presentations.</li>\n<li>Demonstrated work experience in hybrid on-premise and Public Cloud environments (AWS/GCP/Azure)</li>\n<li>Strong understanding of security architectures, secure configuration principles/coding practices, cryptography fundamentals and encryption protocols.</li>\n<li>Experience with common SCM &amp; 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As a subject matter expert with direct experience in a wide range of security technologies, tools, and methodologies, you will play a key role in building toolsets and processes to drive adoption of secure practices across the enterprise.</p>\n<p>The successful candidate will have a proven understanding in enterprise security and AI security and will focus on defining and implementing security guardrails for Generative AI, LLMs, and Agentic frameworks, ensuring safe enterprise adoption.</p>\n<p>Key responsibilities include:</p>\n<ul>\n<li>Defining and implementing security guardrails for Generative AI, LLMs, and Agentic frameworks</li>\n<li>Conducting specialized threat modeling, red teaming, and risk assessments for AI/ML models</li>\n<li>Leading risk management activities, including application risk assessments, design reviews, and mitigation strategies for IT projects</li>\n<li>Engaging throughout the SDLC to identify vulnerabilities, conduct code reviews/penetration testing, and enforce secure coding standards</li>\n<li>Evangelizing AppSec and AI security best practices through developer education, training materials, and outreach</li>\n</ul>\n<p>Qualifications include:</p>\n<ul>\n<li>Bachelor&#39;s degree or higher in Computer Science, Computer Engineering, IT Security or related field</li>\n<li>5+ years&#39; experience working as an Application Security Engineer, Software Engineer, or similar role</li>\n<li>Deep understanding of AI-specific risks (OWASP Top 10 for LLMs) and experience securing applications utilizing LLMs</li>\n<li>Experience working with AI models, Agentic frameworks and security risks associated with AI</li>\n<li>Experience in working with global teams, collaborating on code and presentations</li>\n</ul>\n<p>Preferred qualifications include:</p>\n<ul>\n<li>Demonstrated work experience in hybrid on-premise and Public Cloud environments (AWS/GCP/Azure)</li>\n<li>Strong understanding of security architectures, secure configuration principles/coding practices, cryptography fundamentals and encryption protocols</li>\n<li>Experience with common SCM &amp; CI/CD technologies like GitHub, Jenkins, Artifactory, etc. and integrating Security Scanning and Vulnerability Management into the CI/CD Pipelines</li>\n<li>Familiarity with static and dynamic security analysis tools, and SCA/SBOM solutions</li>\n<li>Hands on experience with Secrets Management &amp; Password Vault technologies such as Delinea Secret Server and/or Hashicorp Vault, etc.</li>\n<li>Strong experience in secure programming in languages such as Python, Java, C++, C#, or similar</li>\n<li>Familiarity with Infrastructure as Code tools (CloudFormation, Terraform, Ansible, etc.)</li>\n<li>Familiarity with web application security testing tools and methodologies</li>\n<li>Knowledge of various security frameworks and standards such as ISO 27001, NIST, OWASP, etc.</li>\n<li>Knowledge of Linux, OS internals and containers is a plus</li>\n<li>Certifications like CISSP, CISM, CompTIA Security+, or CEH are advantageous</li>\n</ul>\n<p>We offer a competitive salary and benefits package, as well as opportunities for professional growth and development.</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_6a75ea8b-5b4","directApply":true,"hiringOrganization":{"@type":"Organization","name":"IT Infrastructure","sameAs":"https://mlp.eightfold.ai","logo":"https://logos.yubhub.co/mlp.eightfold.ai.png"},"x-apply-url":"https://mlp.eightfold.ai/careers/job/755955629908","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["AI-specific risks","Generative AI","LLMs","Agentic frameworks","Security guardrails","Threat modeling","Red teaming","Risk assessments","Application risk assessments","Design reviews","Mitigation strategies","Secure coding standards","Developer education","Training materials","Outreach","Common SCM & CI/CD technologies","GitHub","Jenkins","Artifactory","Security Scanning","Vulnerability Management","Static and dynamic security analysis tools","SCA/SBOM solutions","Secrets Management & Password Vault technologies","Delinea Secret Server","Hashicorp Vault","Secure programming","Python","Java","C++","C#","Infrastructure as Code tools","CloudFormation","Terraform","Ansible","Web application security testing tools","Methodologies","Security frameworks","Standards","ISO 27001","NIST","OWASP","Linux","OS internals","Containers"],"x-skills-preferred":[],"datePosted":"2026-04-18T22:14:06.620Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"London, United Kingdom"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"AI-specific risks, Generative AI, LLMs, Agentic frameworks, Security guardrails, Threat modeling, Red teaming, Risk assessments, Application risk assessments, Design reviews, Mitigation strategies, Secure coding standards, Developer education, Training materials, Outreach, Common SCM & CI/CD technologies, GitHub, Jenkins, Artifactory, Security Scanning, Vulnerability Management, Static and dynamic security analysis tools, SCA/SBOM solutions, Secrets Management & Password Vault technologies, Delinea Secret Server, Hashicorp Vault, Secure programming, Python, Java, C++, C#, Infrastructure as Code tools, CloudFormation, Terraform, Ansible, Web application security testing tools, Methodologies, Security frameworks, Standards, ISO 27001, NIST, OWASP, Linux, OS internals, Containers"},{"@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_10bf8d86-b30"},"title":"Research Engineer, Safeguards Labs","description":"<p><strong>About the Role</strong></p>\n<p>We&#39;re hiring research engineers to define and execute the Labs research agenda. You&#39;ll scope your own projects, run experiments end-to-end, and decide when an idea is ready to hand off to a production team , or when to kill it and move on.</p>\n<p><strong>Responsibilities:</strong></p>\n<ul>\n<li>Lead and contribute to research projects investigating new methods for detecting misuse of Claude, identifying malicious organisations and accounts, strengthening model safeguards, and other safety needs.</li>\n</ul>\n<ul>\n<li>Design and run offline analyses over model usage data to surface abuse patterns, build classifiers and detection systems, and evaluate their effectiveness.</li>\n</ul>\n<ul>\n<li>Develop and iterate on prototypes that could eventually feed signals into the real-time safeguards path, partnering with engineers on tech transfer.</li>\n</ul>\n<ul>\n<li>Contribute to a broader research portfolio investigating methods for detecting abusive behaviour in chat-based or agentive workflows, and for training the model to robustly refrain from dangerous responses or behaviours without over-refusing.</li>\n</ul>\n<ul>\n<li>Build evaluations and methodologies for measuring whether safeguards actually work, including in agentic settings.</li>\n</ul>\n<ul>\n<li>Write up findings clearly so they inform decisions across Trust &amp; Safety, research, and product teams.</li>\n</ul>\n<p><strong>You may be a good fit if you:</strong></p>\n<ul>\n<li>Have a track record of independently driving research projects from ambiguous problem statements to concrete results, ideally in AI, ML, security, integrity, or a related technical field.</li>\n</ul>\n<ul>\n<li>Are comfortable scoping your own work and switching between research, engineering, and analysis as a project demands.</li>\n</ul>\n<ul>\n<li>Have working familiarity with how large language models operate , sampling, prompting, training , even if LLMs aren&#39;t your primary background.</li>\n</ul>\n<ul>\n<li>Are proficient in Python and comfortable working with large datasets.</li>\n</ul>\n<ul>\n<li>Care about the societal impacts of AI and want your work to directly reduce real-world harm.</li>\n</ul>\n<p><strong>Strong candidates may also have:</strong></p>\n<ul>\n<li>Experience building and training machine learning models, including classifiers for abuse, fraud, integrity, or security applications.</li>\n</ul>\n<ul>\n<li>Knowledge of evaluation methodologies for language models and experience designing evals.</li>\n</ul>\n<ul>\n<li>Experience with agentic environments and evaluating model behaviour in them.</li>\n</ul>\n<ul>\n<li>Background in trust and safety, integrity, fraud detection, threat intelligence, or adversarial ML.</li>\n</ul>\n<ul>\n<li>Experience with red teaming, jailbreak research, or interpretability methods like steering vectors.</li>\n</ul>\n<ul>\n<li>A history of taking research prototypes and transferring them into production systems.</li>\n</ul>\n<p><strong>Logistics</strong></p>\n<ul>\n<li>Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience</li>\n</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<p><strong>Benefits</strong></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><strong>Visa Sponsorship</strong></p>\n<ul>\n<li>We do sponsor visas! However, we aren&#39;t able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_10bf8d86-b30","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/5191785008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$350,000-$850,000 USD","x-skills-required":["Python","Machine learning","Large language models","Security","Integrity"],"x-skills-preferred":["Experience building and training machine learning models","Knowledge of evaluation methodologies for language models","Experience with agentic environments","Background in trust and safety","Experience with red teaming"],"datePosted":"2026-04-18T15:55:10.055Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA | New York City, NY"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, Machine learning, Large language models, Security, Integrity, Experience building and training machine learning models, Knowledge of evaluation methodologies for language models, Experience with agentic environments, Background in trust and safety, Experience with red teaming","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":350000,"maxValue":850000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_a0355e9d-a71"},"title":"Research Lead, Training Insights","description":"<p>As a Research Lead on the Training Insights team, you&#39;ll develop the strategy for, and lead execution on, how we measure and characterise model capabilities across training and deployment. This is a hands-on leadership role: you&#39;ll drive original research into new evaluation methodologies while leading a small team of researchers and research engineers doing the same.</p>\n<p>Your work will span the full lifecycle of model development. You&#39;ll research and build new long-horizon evaluations that test the boundaries of what our models can achieve, develop novel approaches to measuring emerging capabilities, and deepen our understanding of how those capabilities develop , both during production RL training and after. You&#39;ll also take a cross-organisational view, working across Reinforcement Learning, Pretraining, Inference, Product, Alignment, Safeguards, and other teams to map the landscape of model evaluations at Anthropic and identify critical gaps in coverage.</p>\n<p>This role carries significant visibility and impact. You&#39;ll help shape the evaluation narrative for model releases, contributing directly to how Anthropic communicates about its models to both internal and external audiences. Done well, you will change how the industry measures and understands model capabilities, significantly furthering our safety mission.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Build new novel and long-horizon evaluations</li>\n<li>Develop novel measurement approaches for understanding how model capabilities emerge and evolve during RL training</li>\n<li>Lead strategic evaluation coverage across the company</li>\n<li>Shape the evaluation narrative for model releases</li>\n<li>Lead and mentor a small team of researchers and research engineers, setting research direction and fostering a culture of rigorous, creative research</li>\n<li>Design evaluation frameworks that balance scientific rigor with the practical demands of production training schedules</li>\n<li>Build and maintain relationships across Anthropic&#39;s research organisation to ensure evaluation insights inform training and deployment decisions</li>\n<li>Contribute to the broader research community through publications, open-source contributions, or external engagement on evaluation best practices</li>\n</ul>\n<p>You may be a good fit if you:</p>\n<ul>\n<li>Have significant experience designing and running evaluations for large language models or similar complex ML systems</li>\n<li>Have led technical projects or teams, either formally or through sustained ownership of critical research directions</li>\n<li>Are equally comfortable designing experiments and writing code,you can move between research and implementation fluidly</li>\n<li>Think strategically about what to measure and why, not just how to measure it</li>\n<li>Can synthesise information across multiple teams and workstreams to form a coherent picture of model capabilities</li>\n<li>Communicate complex technical findings clearly to both technical and non-technical audiences</li>\n<li>Are results-oriented and thrive in fast-paced environments where priorities shift based on research findings</li>\n<li>Care deeply about AI safety and want your work to directly influence how capable AI systems are developed and deployed</li>\n</ul>\n<p>Strong candidates may also have:</p>\n<ul>\n<li>Experience building evaluations for long-horizon or agentic tasks</li>\n<li>Deep familiarity with Reinforcement Learning training dynamics and how model behaviour changes during training</li>\n<li>Published research in machine learning evaluation, benchmarking, or related areas</li>\n<li>Experience with safety evaluation frameworks and red teaming methodologies</li>\n<li>Background in psychometrics, experimental psychology, or other measurement-focused disciplines</li>\n<li>A track record of communicating evaluation results to inform high-stakes decisions about model development or deployment</li>\n<li>Experience managing or mentoring researchers and engineers</li>\n</ul>\n<p>Representative projects:</p>\n<ul>\n<li>Designing and implementing a suite of long-horizon evaluations that test model capabilities on tasks requiring sustained reasoning, planning, and tool use over extended interactions</li>\n<li>Building systems to track capability development across RL training checkpoints, surfacing insights about when and how specific capabilities emerge</li>\n<li>Conducting a cross-org audit of evaluation coverage, identifying blind spots, and prioritising new evaluations to fill critical gaps across Pretraining, RL, Inference, and Product</li>\n<li>Developing the evaluation methodology and narrative for a major model release, working with research leads and communications to clearly characterise model capabilities and limitations</li>\n<li>Researching and prototyping novel evaluation approaches for capabilities that are difficult to measure with existing benchmarks</li>\n<li>Leading a team effort to build reusable evaluation infrastructure that serves multiple teams across the research organisation</li>\n</ul>\n<p>The annual compensation range for this role is $850,000.</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_a0355e9d-a71","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/5139654008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$850,000-$850,000","x-skills-required":["AI","Machine Learning","Reinforcement Learning","Evaluation Methodologies","Research Leadership","Team Management","Communication","Results-Oriented","Fast-Paced Environments"],"x-skills-preferred":["Long-Horizon Evaluations","Agentic Tasks","Safety Evaluation Frameworks","Red Teaming Methodologies","Psychometrics","Experimental Psychology","Measurement-Focused Disciplines"],"datePosted":"2026-04-18T15:46:21.084Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Remote-Friendly (Travel Required) | San Francisco, CA; San Francisco, CA | New York City, NY"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"AI, Machine Learning, Reinforcement Learning, Evaluation Methodologies, Research Leadership, Team Management, Communication, Results-Oriented, Fast-Paced Environments, Long-Horizon Evaluations, Agentic Tasks, Safety Evaluation Frameworks, Red Teaming Methodologies, Psychometrics, Experimental Psychology, Measurement-Focused Disciplines","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":850000,"maxValue":850000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_bdf949b3-c66"},"title":"Databricks Enterprise Lead Security Architect -   Principal IT Software Engineer","description":"<p>We are seeking a highly skilled Lead Security Architect to join our team within Databricks IT. As a Lead Security Architect, you will be responsible for designing and implementing a secure and scalable architecture to protect our corporate assets. You will focus on key areas of IT security, including Identity and Access Management, Zero Trust architecture, and endpoint security, while also working to secure critical business applications and sensitive data.</p>\n<p>Your expertise will be crucial in building proactive security strategies that align with our business goals and protect the company from an ever-evolving threat landscape. This position demands deep expertise in security principles and a comprehensive understanding of the entire infrastructure stack and IAM systems to design robust, future-ready security solutions.</p>\n<p>You will be instrumental in safeguarding our systems&#39; resilience and integrity against ever-evolving cyber threats. You will play a critical role in shaping our security strategy for modern platforms across AWS, Azure, GCP, network infrastructure, storage, and SaaS solutions, help establish a strong least privilege (PoLP) model, providing specialized IAM expertise, and securely supporting SaaS with sensitive information (NHI).</p>\n<p>You will also be a key contributor in building our internal strategy for secure AI development. Additionally, you will support the secure integration of SaaS platforms such as Google Workspace, collaboration tools, and GTM systems, maintaining alignment with enterprise security standards.</p>\n<p>Close collaboration with cross-functional teams is essential to embed security throughout the technology stack.</p>\n<p>The impact you will have:</p>\n<ul>\n<li>Design and implement secure, scalable reference architectures for the Databricks IT across Cloud Infra (Compute, DBs, Network, Storage), SaaS, Custom Built Applications, Data &amp; AI systems.</li>\n<li>Establish and enforce security controls for: Core Security Areas: - Databricks Workspace Management: Workspace isolation, Unity Catalog for data governance.</li>\n<li>Secure Networking: VPC configs, PrivateLink, IP Allow Lists.</li>\n<li>Identity and Access Management (IAM): SSO, SCIM user provisioning, RBAC via Un, Strong MFA best practices for enterprise identities and customers.</li>\n<li>Data Encryption: At rest and in transit, customer-managed keys for critical assets.</li>\n<li>Data Exfiltration Prevention: Admin console settings, VPC endpoint controls.</li>\n<li>Cluster Security: User isolation, compliance with enhanced security monitoring/Compliance Security Profiles (HIPAA, PCI-DSS, FedRAMP).</li>\n<li>Offensive Security: Test and challenge the effectiveness of the organization’s security defenses by mimicking the tactics, techniques, and procedures used by actual attackers.</li>\n<li>Specialized Security Functions: - Non-human Identity Management: Design and implement secure authentication and authorization for automated systems (service accounts, API keys, machine identities), focusing on automation and integration with existing identity management systems.</li>\n<li>IAM Best Practices: Develop and document comprehensive Identity and Access Management policies, including user provisioning, de-provisioning, access reviews, privileged access management, and multi-factor authentication, ensuring security and compliance.</li>\n<li>Data Loss Prevention (DLP): Implement DLP solutions to identify, monitor, and protect sensitive data across endpoints, networks, and cloud environments, preventing unauthorized access, use, or transmission.</li>\n<li>SaaS Proxy Design and Implementation: Design and implement cloud-based proxies for SaaS applications (SASE solutions) to provide secure access, enforce security policies, monitor user activity, and protect against threats.</li>\n<li>Cloud Infrastructure Best Practices: Establish and document best practices for VPC configurations, cloud networking, and infrastructure as code using Terraform, ensuring secure network segmentation, routing, firewalls, and VPNs for consistent, automated, and secure deployments.</li>\n<li>Least Privilege Access for Data Security: Design and implement data security controls based on the principle of least privilege, ensuring users and systems have only the minimum necessary access through fine-grained controls, data classification, and regular access reviews.</li>\n<li>Guide internal IT on Databricks’ security and compliance certifications (SOC 2, ISO 27001/27017/27018, HIPAA, PCI-DSS, FedRAMP), and support security reviews/audits.</li>\n<li>Support incident response, vulnerability management, threat modeling, and red teaming using audit logs, cluster policies, and enhanced monitoring.</li>\n<li>Stay current on industry trends and emerging threats in GenAI, AI Agentic flow, MCPs to enhance security posture.</li>\n<li>Advise executive leadership on security architecture, risks, and mitigation.</li>\n<li>Mentor security engineers and developers on secure design and best practices.</li>\n</ul>\n<p>What we look for:</p>\n<ul>\n<li>Bachelor’s degree in Computer Science, Information Security, Engineering, or a related field</li>\n<li>Master’s degree in Computer Science specifically in Information Security or a related discipline is strongly preferred</li>\n<li>Minimum 12 years in cybersecurity, with 5+ in security architecture or senior technical roles.</li>\n<li>Experience in FedRAMP High systems/ GovCloud preferred.</li>\n<li>Must have direct experience designing and securing enterprise platforms in complex multi-cloud environments, deep knowledge of enterprise architecture and security features (control plane/data plane separation, network infra, workspace hardening, network segmentation/ isolation), and hands-on experience automating security controls with Terraform and scripting.</li>\n<li>Proven expertise securing data analytics pipelines, SaaS integrations, and workload isolation in enterprise ecosystems.</li>\n<li>Experience with Enterprise Security Analysis Tools and monitoring/security policy optimization.</li>\n<li>Deep experience in threat modeling, design, PoC, and implementing large-scale enterprise solutions.</li>\n<li>Extensive hands-on experience in AWS cloud security, network security, with knowledge of Zero Trust, Data Protection, and Appsec.</li>\n<li>Strong understanding of enterprise IAM systems (Okta, SailPoint, VDI, Entra ID) and Data Protection.</li>\n<li>Expert experience with SIEM platforms, XDR, and cloud-native threat detection tools.</li>\n<li>Expert in web application security, OWASP, API security, and secure design and testing.</li>\n<li>Hands-on experience with security automation is required, with proficiency in AI-assisted development, Python, Cursor, Lambda, Terraform, or comparable scripting/IaC tools for operational efficiency.</li>\n<li>Industry certifications like CISSP, CCSP, CEH, AWS Certified Security – Specialty, AWS Certified Solutions Architect – Professional, or AWS Certified Advanced Networking – Specialty (or equivalent) are preferred.</li>\n<li>Ability to influence stakeholders and drive alignment.</li>\n<li>Strategic thinker with a passion for security innovation, continuous improvement, and building scalable defenses.</li>\n</ul>\n<p>Pay Range Transparency</p>\n<p>Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above.</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_bdf949b3-c66","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Databricks","sameAs":"https://databricks.com","logo":"https://logos.yubhub.co/databricks.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/databricks/jobs/8207910002","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Security Architecture","Identity and Access Management","Zero Trust","Endpoint Security","Data Encryption","Data Exfiltration Prevention","Cluster Security","Offensive Security","Non-human Identity Management","IAM Best Practices","Data Loss Prevention","SaaS Proxy Design and Implementation","Cloud Infrastructure Best Practices","Least Privilege Access for Data Security","Guide internal IT on Databricks’ security and compliance certifications","Support incident response, vulnerability management, threat modeling, and red teaming","Stay current on industry trends and emerging threats in GenAI, AI Agentic flow, MCPs","Advise executive leadership on security architecture, risks, and mitigation","Mentor security engineers and developers on secure design and best practices"],"x-skills-preferred":["Terraform","Python","Cursor","Lambda","AWS cloud security","Network security","Data Protection","Appsec","SIEM platforms","XDR","cloud-native threat detection tools","Web application security","OWASP","API security","Secure design and testing","AI-assisted development","Security automation","Scripting/IaC tools","CISSP","CCSP","CEH","AWS Certified Security – Specialty","AWS Certified Solutions Architect – Professional","AWS Certified Advanced Networking – Specialty"],"datePosted":"2026-04-18T15:45:19.828Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Mountain View, California; San Francisco, California"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Security Architecture, Identity and Access Management, Zero Trust, Endpoint Security, Data Encryption, Data Exfiltration Prevention, Cluster Security, Offensive Security, Non-human Identity Management, IAM Best Practices, Data Loss Prevention, SaaS Proxy Design and Implementation, Cloud Infrastructure Best Practices, Least Privilege Access for Data Security, Guide internal IT on Databricks’ security and compliance certifications, Support incident response, vulnerability management, threat modeling, and red teaming, Stay current on industry trends and emerging threats in GenAI, AI Agentic flow, MCPs, Advise executive leadership on security architecture, risks, and mitigation, Mentor security engineers and developers on secure design and best practices, Terraform, Python, Cursor, Lambda, AWS cloud security, Network security, Data Protection, Appsec, SIEM platforms, XDR, cloud-native threat detection tools, Web application security, OWASP, API security, Secure design and testing, AI-assisted development, Security automation, Scripting/IaC tools, CISSP, CCSP, CEH, AWS Certified Security – Specialty, AWS Certified Solutions Architect – Professional, AWS Certified Advanced Networking – Specialty"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_6e48ec86-b97"},"title":"Security Labs Engineer","description":"<p><strong>About the Role</strong></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<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_0ae6f8dc-4fd"},"title":"Staff Engineer, AI Security","description":"<p>Join the team as Twilio&#39;s next Staff Engineer, AI Security.</p>\n<p>As a Staff Engineer, AI Security on the AppSec team, you&#39;ll lead autonomous defense for the AI lifecycle. Build multi-agent frameworks and secure gateways while integrating real-time security gates and identity standards. By mentoring Security and R&amp;D to define the MLSecOps roadmap, you&#39;ll ensure a &#39;secure-by-default&#39; future for agentic workflows and resilient AI innovation.</p>\n<p>Responsibilities:</p>\n<p>Serve as the primary subject matter expert for all AI and machine learning security initiatives across security and R&amp;D.</p>\n<p>Design and manage AI gateways to provide a centralized control plane for authentication and authorization and rate limiting across all model and tool interactions.</p>\n<p>Build and maintain an autonomous security agentic framework that utilizes multi agent orchestration for end to end investigation and alert triage and remediation.</p>\n<p>Develop agentic identity models using OAuth 2.1 to propagate identity across trust boundaries and prevent the confused deputy problem.</p>\n<p>Help govern the AI augmented software development lifecycle by integrating real time security gates into the developer environment and CI/CD pipeline.</p>\n<p>Manage Agentic Security Solutions that secure AI lifecycle and manage AI workloads at runtime.</p>\n<p>Author company wide AI security standards and implement these security checks across Twilio&#39;s stack.</p>\n<p>Implement human in the loop checkpoints and transactional safety protocols for high impact or destructive agentic actions.</p>\n<p>Partner with engineering leadership to set the long term roadmap for identity centric security and automated posture management.</p>\n<p>Act as a knowledge multiplier by mentoring security engineers and developing secure by default paved road templates for R&amp;D teams</p>\n<p>Qualifications:</p>\n<p>8+ years of experience in security engineering with at least 3 years focused on AI or machine learning security operations (MLSecOps).</p>\n<p>Expertise in orchestrating multi-agent systems with AWS Strands, LangGraph, and CrewAI, specializing in runtime isolation, PII redaction, and defending against indirect prompt injection in agentic environments.</p>\n<p>Hands-on experience with AI-specific frameworks (e.g., MITRE ATLAS, MAESTRO, OWASP Top 10 for LLMs/Agents/MCP) to threat model and defend against a wide spectrum of risks, including direct/indirect prompt injection, training data poisoning, tool poisoning, and data exfiltration within agentic workflows.</p>\n<p>Proficiency in securing end-to-end AI pipelines, from data ingestion and training to model deployment and monitoring.</p>\n<p>Strong communication skills to translate complex AI risks into actionable business logic for stakeholders.</p>\n<p>Desired:</p>\n<p>Hands-on experience in modern application security tooling including SAST and SCA and DAST with experience adapting these tools to catch AI specific vulnerabilities like indirect prompt injection.</p>\n<p>Expertise in identity standards including OAuth 2.1 and PKCE.</p>\n<p>Experience with AI Red Teaming and conducting adversarial simulations against Large Language Models (LLMs) and agentic systems.</p>\n<p>Proficiency in at least one general programming language (Python, Go, etc) with experience in container security and workload isolation.</p>\n<p>Proven ability to operate with autonomy and drive high impact outcomes in ambiguous environments by identifying and executing on critical projects without predefined roadmaps or direct supervision.</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_0ae6f8dc-4fd","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Twilio","sameAs":"https://www.twilio.com/","logo":"https://logos.yubhub.co/twilio.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/twilio/jobs/7821462","x-work-arrangement":"remote","x-experience-level":"staff","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["security engineering","AI and machine learning security","multi-agent systems","AWS Strands","LangGraph","CrewAI","runtime isolation","PII redaction","indirect prompt injection","AI-specific frameworks","MITRE ATLAS","MAESTRO","OWASP Top 10 for LLMs/Agents/MCP","end-to-end AI pipelines","data ingestion","training","model deployment","monitoring","strong communication skills"],"x-skills-preferred":["modern application security tooling","SAST and SCA and DAST","identity standards","OAuth 2.1","PKCE","AI Red Teaming","adversarial simulations","Large Language Models","container security","workload isolation"],"datePosted":"2026-04-18T15:44:10.579Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Remote - Ireland"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"security engineering, AI and machine learning security, multi-agent systems, AWS Strands, LangGraph, CrewAI, runtime isolation, PII redaction, indirect prompt injection, AI-specific frameworks, MITRE ATLAS, MAESTRO, OWASP Top 10 for LLMs/Agents/MCP, end-to-end AI pipelines, data ingestion, training, model deployment, monitoring, strong communication skills, modern application security tooling, SAST and SCA and DAST, identity standards, OAuth 2.1, PKCE, AI Red Teaming, adversarial simulations, Large Language Models, container security, workload isolation"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_d63f049e-ad7"},"title":"Security Lead, Agentic Red Team","description":"<p>Job Title: Security Lead, Agentic Red Team</p>\n<p>We&#39;re a team of scientists, engineers, and machine learning experts working together to advance the state of the art in artificial intelligence. Our mission is to close the &#39;Agentic Launch Gap&#39;; the critical window where novel AI capabilities outpace traditional security reviews.</p>\n<p>As the Security Lead for the Agentic Red Team, you will direct a specialized unit of AI Researchers and Offensive Security Engineers focused on adversarial AI and agentic exploitation. Operating as a technical player-coach, you will architect complex, multi-turn attack scenarios while managing cross-functional partnerships with Product Area leads and Google security to influence launch criteria.</p>\n<p>Key Responsibilities:</p>\n<ul>\n<li>Direct Agile Offensive Security: Lead a specialized red team focused on rapid, high-impact engagements targeting production-level AI models and systems.</li>\n<li>Perform Complex AI Exploitation: Develop and carry out advanced attack sequences that focus on vulnerabilities unique to GenAI, such as escalating privileges through tool usage, poisoning data, and executing multi-turn prompt injections.</li>\n<li>Design Automated Validation Systems: Collaborate with Google teams to engineer &#39;Auto RedTeaming&#39; solutions that transform manual vulnerability discoveries into robust, automated regression testing frameworks.</li>\n<li>Engineer Technical Countermeasures: Create innovative defense-in-depth frameworks and control systems to mitigate agentic logic errors and non-deterministic model behaviors.</li>\n<li>Manage Threat Intelligence Assets: Develop and oversee an evolving inventory of exploit primitives and agent-specific attack patterns used to establish release criteria and evaluate model security benchmarks.</li>\n<li>Establish Security Scope: Collaborate with Google for conventional infrastructure protection, allowing the team to concentrate solely on agentic logic, model inference, and AI-centric exploits.</li>\n</ul>\n<p>About You:</p>\n<ul>\n<li>Bachelor&#39;s degree in Computer Science, Information Security, or equivalent practical experience.</li>\n<li>Experience in Red Teaming, Offensive Security, or Adversarial Machine Learning.</li>\n<li>Deep technical understanding of LLM architectures and agentic workflows (e.g., chain-of-thought reasoning, tool usage).</li>\n<li>Proven ability to work in a consulting capacity with product teams, driving security improvements in fast-paced release cycles.</li>\n<li>Experience managing or technically leading small, high-performance engineering teams.</li>\n</ul>\n<p>In addition, the following would be an advantage:</p>\n<ul>\n<li>Hands-on experience developing exploits for GenAI models (e.g., prompt injection, adversarial examples, training data extraction).</li>\n<li>Familiarity with AI safety benchmarks and evaluation frameworks.</li>\n<li>Experience writing code (Python, Go, or C++) to build automated security tools or fuzzers.</li>\n<li>Ability to communicate complex probabilistic risks to executive stakeholders and engineering teams effectively.</li>\n</ul>\n<p>The US base salary range for this full-time position is between $248,000 - $349,000 + bonus + equity + benefits.</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_d63f049e-ad7","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Google DeepMind","sameAs":"https://deepmind.com/","logo":"https://logos.yubhub.co/deepmind.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/deepmind/jobs/7560787","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$248,000 - $349,000 + bonus + equity + benefits","x-skills-required":["Bachelor's degree in Computer Science, Information Security, or equivalent practical experience","Experience in Red Teaming, Offensive Security, or Adversarial Machine Learning","Deep technical understanding of LLM architectures and agentic workflows","Proven ability to work in a consulting capacity with product teams","Experience managing or technically leading small, high-performance engineering teams"],"x-skills-preferred":["Hands-on experience developing exploits for GenAI models","Familiarity with AI safety benchmarks and evaluation frameworks","Experience writing code (Python, Go, or C++) to build automated security tools or fuzzers","Ability to communicate complex probabilistic risks to executive stakeholders and engineering teams effectively"],"datePosted":"2026-03-16T14:41:55.843Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Mountain View, California, US; 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Our mission is to close the &#39;Agentic Launch Gap&#39;,the critical window where novel AI capabilities outpace traditional security reviews.</p>\n<p><strong>The Role</strong> As a Senior Security Engineer on the Agentic Red Team, you will be the primary technical executor of our adversarial engagements. You will work &#39;in the room&#39; with product builders, identifying architectural flaws during the design phase long before formal reviews begin.</p>\n<p><strong>Key Responsibilities:</strong></p>\n<ul>\n<li>Execute Agile Red Teaming: Conduct rapid, high-impact security assessments on agentic services, focusing on vulnerabilities unique to GenAI such as prompt injection, tool-use escalation, and autonomous lateral movement.</li>\n<li>Develop Advanced Exploits: Engineer and execute complex attack sequences that exploit non-deterministic model behaviors, agentic logic errors, and data poisoning vectors.</li>\n<li>Build Automated Defenses: Write code to transform manual vulnerability discoveries into automated regression testing frameworks (&#39;Auto Red Teaming&#39;) that prevent regression in future model versions.</li>\n<li>Embed with Product Teams: Partner directly with developers during the design and build phases to provide immediate feedback, effectively shortening the feedback loop between offensive findings and defensive engineering.</li>\n<li>Curate Threat Intelligence: Maintain and expand a library of agent-specific attack patterns and exploit primitives to establish robust release criteria for new models.</li>\n</ul>\n<p><strong>About You</strong> In order to set you up for success as a Software Engineer at Google DeepMind, we look for the following skills and experience:</p>\n<ul>\n<li>Bachelor&#39;s degree in Computer Science, Information Security, or equivalent practical experience.</li>\n<li>Experience in Red Teaming, Offensive Security, or Adversarial Machine Learning.</li>\n<li>Strong coding skills in Python, Go, or C++ with experience building security tools or automation.</li>\n<li>Technical understanding of LLM architectures, agentic workflows (e.g., chain-of-thought reasoning), and common AI vulnerability classes.</li>\n</ul>\n<p><strong>Preferred Qualifications</strong></p>\n<ul>\n<li>Hands-on experience developing exploits for GenAI models (e.g., prompt injection, adversarial examples, training data extraction).</li>\n<li>Experience working in a consulting capacity with product teams or in a fast-paced &#39;startup-like&#39; environment.</li>\n<li>Familiarity with AI safety benchmarks, evaluation frameworks, and fuzzing techniques.</li>\n<li>Ability to translate complex probabilistic risks into actionable engineering fixes for developers.</li>\n</ul>\n<p><strong>Salary &amp; Benefits</strong> The US base salary range for this full-time position is between $166,000 - $244,000 + bonus + equity + benefits.</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_f73f108d-30a","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Google DeepMind","sameAs":"https://deepmind.com/","logo":"https://logos.yubhub.co/deepmind.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/deepmind/jobs/7596438","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$166,000 - $244,000 + bonus + equity + benefits","x-skills-required":["Python","Go","C++","Red Teaming","Offensive Security","Adversarial Machine Learning","LLM architectures","agentic workflows","chain-of-thought reasoning","AI vulnerability classes"],"x-skills-preferred":["prompt injection","adversarial examples","training data extraction","AI safety benchmarks","evaluation frameworks","fuzzing techniques"],"datePosted":"2026-03-16T14:39:43.939Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Mountain View, California, US; New York City, New York, US; Zurich, Switzerland"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, Go, C++, Red Teaming, Offensive Security, Adversarial Machine Learning, LLM architectures, agentic workflows, chain-of-thought reasoning, AI vulnerability classes, prompt injection, adversarial examples, training data extraction, AI safety benchmarks, evaluation frameworks, fuzzing techniques","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":166000,"maxValue":244000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_c33b2d78-cc9"},"title":"Research Lead, Training Insights","description":"<p><strong>About the role</strong></p>\n<p>As a Research Lead on the Training Insights team, you&#39;ll develop the strategy for, and lead execution on, how we measure and characterise model capabilities across training and deployment. This is a hands-on leadership role: you&#39;ll drive original research into new evaluation methodologies while leading a small team of researchers and research engineers doing the same.</p>\n<p>Your work will span the full lifecycle of model development. You&#39;ll research and build new long-horizon evaluations that test the boundaries of what our models can achieve, develop novel approaches to measuring emerging capabilities, and deepen our understanding of how those capabilities develop — both during production RL training and after. You&#39;ll also take a cross-organisational view, working across Reinforcement Learning, Pretraining, Inference, Product, Alignment, Safeguards, and other teams to map the landscape of model evaluations at Anthropic and identify critical gaps in coverage.</p>\n<p>This role carries significant visibility and impact. You&#39;ll help shape the evaluation narrative for model releases, contributing directly to how Anthropic communicates about its models to both internal and external audiences. Done well, you will change how the industry measures and understands model capabilities, significantly furthering our safety mission.</p>\n<p><strong>Responsibilities:</strong></p>\n<ul>\n<li>Build new novel and long-horizon evaluations</li>\n<li>Develop novel measurement approaches for understanding how model capabilities emerge and evolve during RL training</li>\n<li>Lead strategic evaluation coverage across the company</li>\n<li>Shape the evaluation narrative for model releases</li>\n<li>Lead and mentor a small team of researchers and research engineers, setting research direction and fostering a culture of rigorous, creative research</li>\n<li>Design evaluation frameworks that balance scientific rigor with the practical demands of production training schedules</li>\n<li>Build and maintain relationships across Anthropic&#39;s research organisation to ensure evaluation insights inform training and deployment decisions</li>\n<li>Contribute to the broader research community through publications, open-source contributions, or external engagement on evaluation best practices</li>\n</ul>\n<p><strong>You may be a good fit if you:</strong></p>\n<ul>\n<li>Have significant experience designing and running evaluations for large language models or similar complex ML systems</li>\n<li>Have led technical projects or teams, either formally or through sustained ownership of critical research directions</li>\n<li>Are equally comfortable designing experiments and writing code—you can move between research and implementation fluidly</li>\n<li>Think strategically about what to measure and why, not just how to measure it</li>\n<li>Can synthesise information across multiple teams and workstreams to form a coherent picture of model capabilities</li>\n<li>Communicate complex technical findings clearly to both technical and non-technical audiences</li>\n<li>Are results-oriented and thrive in fast-paced environments where priorities shift based on research findings</li>\n<li>Care deeply about AI safety and want your work to directly influence how capable AI systems are developed and deployed</li>\n</ul>\n<p><strong>Strong candidates may also have:</strong></p>\n<ul>\n<li>Experience building evaluations for long-horizon or agentic tasks</li>\n<li>Deep familiarity with Reinforcement Learning training dynamics and how model behaviour changes during training</li>\n<li>Published research in machine learning evaluation, benchmarking, or related areas</li>\n<li>Experience with safety evaluation frameworks and red teaming methodologies</li>\n<li>Background in psychometrics, experimental psychology, or other measurement-focused disciplines</li>\n<li>A track record of communicating evaluation results to inform high-stakes decisions about model development or deployment</li>\n<li>Experience managing or mentoring researchers and engineers</li>\n</ul>\n<p><strong>Representative projects:</strong></p>\n<ul>\n<li>Designing and implementing a suite of long-horizon evaluations that test model capabilities on tasks requiring sustained reasoning, planning, and tool use over extended interactions</li>\n<li>Building systems to track capability development across RL training checkpoints, surfacing insights about when and how specific capabilities emerge</li>\n<li>Conducting a cross-org audit of evaluation coverage, identifying blind spots, and prioritising new evaluations to fill critical gaps across Pretraining, RL, Inference, and Product</li>\n<li>Developing the evaluation methodology and narrative for a major model release, working with research leads and communications to clearly characterise model capabilities and limitations</li>\n<li>Researching and prototyping novel evaluation approaches for capabilities that are difficult to measure with existing benchmarks</li>\n<li>Leading a team effort to build reusable evaluation infrastructure that serves multiple teams across the research organisation</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. 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If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.</p>\n<ul>\n<li>Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts</li>\n</ul>\n<ul>\n<li>Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)</li>\n</ul>\n<ul>\n<li>401(k) retirement plan with employer match</li>\n</ul>\n<ul>\n<li>Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)</li>\n</ul>\n<ul>\n<li>Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees</li>\n</ul>\n<ul>\n<li>13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)</li>\n</ul>\n<ul>\n<li>Mental health and wellness support</li>\n</ul>\n<ul>\n<li>Employer-paid basic life and disability coverage</li>\n</ul>\n<ul>\n<li>Annual learning and development stipend to fuel your professional growth</li>\n</ul>\n<ul>\n<li>Daily meals in our offices, and meal delivery credits as eligible</li>\n</ul>\n<ul>\n<li>Relocation support for eligible employees</li>\n</ul>\n<ul>\n<li>Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.</li>\n</ul>\n<p>More details about our benefits are available to candidates during the hiring process.</p>\n<p>This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.</p>\n<p><strong>About the team</strong></p>\n<p>The Safety Systems org ensures that OpenAI’s most capable models can be responsibly developed and deployed. We build evaluations, safeguards, and safety frameworks that help our models behave as intended in real-world settings.</p>\n<p>The Preparedness team is an important part of the Safety Systems org at OpenAI, and is guided by OpenAI’s Preparedness Framework.</p>\n<p>Frontier AI models have the potential to benefit all of humanity, but also pose increasingly severe risks. To ensure that AI promotes positive change, the Preparedness team helps us prepare for the development of increasingly capable frontier AI models. This team is tasked with identifying, tracking, and preparing for catastrophic risks related to frontier AI models.</p>\n<p>The mission of the Preparedness team is to:</p>\n<ol>\n<li>Closely monitor and predict the evolving capabilities of frontier AI systems, with an eye towards risks whose impact could be catastrophic</li>\n<li>Ensure we have concrete procedures, infrastructure and partnerships to mitigate these risks and to safely handle the development of powerful AI systems</li>\n</ol>\n<p>Preparedness tightly connects capability assessment, evaluations, and internal red teaming, and mitigations for frontier models, as well as overall coordination on AGI preparedness. This is fast paced, exciting work that has far reaching importance for the company and for society.</p>\n<p><strong>About the role</strong></p>\n<p>This role leads the Automated Red Teaming (ART) effort: building scalable, research-driven systems that continuously discover failure modes in our models and mitigations — and translate those findings into actionable, production-facing improvements. The goal is to maximize counterfactual reduction in expected harm by finding the highest-leverage, least-covered weaknesses early and reliably.</p>\n<p><strong>In this role you will</strong></p>\n<p>You will own the research and technical direction for automated red teaming across catastrophic risk areas, with an initial emphasis on:</p>\n<ul>\n<li>Automated classifier jailbreak discovery (cyber and bio)</li>\n<li>Automated bio threat-development elicitation (worst-feasible planning uplift)</li>\n<li>CoT monitoring evasion probing (and adjacent loss-of-control evaluations)</li>\n</ul>\n<p>You will partner tightly with:</p>\n<ul>\n<li>Vertical risk teams (Cyber, Bio, Loss of Control) to define threat models, prioritize targets, and land mitigations</li>\n<li>The Classifiers team to turn discovered attacks into training data, evals, and measurable robustness gains</li>\n<li>Product / eng / safety stakeholders to ensure ART outputs are operationally useful (not just interesting)</li>\n</ul>\n<p><strong>You might thrive in this role if you:</strong></p>\n<ul>\n<li>Feel a strong pull toward AI safety, and you’re motivated by reducing real-world catastrophic risk (not just publishing cool results)</li>\n<li>Love breaking systems (responsibly) — you get energy from finding weird, high-severity failure modes and turning them into concrete fixes</li>\n<li>Have strong applied research instincts, especially around evaluations: you’re good at designing experiments that are reproducible, interpretable, and hard to fool</li>\n<li>Bring hands-on experience with LLMs and agents, including multi-turn behaviors, tool use, and the ways models adapt to constraints</li>\n<li>Are comfortable building scalable automation, not just prototypes — you can turn red-teaming ideas into pipelines that run continuously and produce high-signal outputs</li>\n<li>Have solid software engineering fundamentals (data structures, algorithms, testing discipline) and you can work effectively in a production-adjacent environment</li>\n<li>Think in threat models and incentives, and you naturally ask “what would an attacker do next?” or “how would this fail under pressure?”</li>\n<li>Can translate messy findings into action, communicating clearly with researchers, engineers, product, and policy — and driving alignment on what to fix first</li>\n<li>Care about efficiency and prioritization, and you’re happy to say “no” to low-level</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_8ee55a18-4c1","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/bf7d2623-7846-410c-87f8-c628915ec16c","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$295K – $445K","x-skills-required":["Applied research","Automated red teaming","Catastrophic risk assessment","Classifier jailbreak discovery","Cybersecurity","Data structures","Evaluations","LLMs and agents","Loss-of-control evaluations","Multi-turn behaviors","Red teaming","Scalable automation","Software engineering","Threat models","Tool use"],"x-skills-preferred":["Bio threat-development elicitation","CoT monitoring evasion probing","Loss-of-control evaluations","Multi-turn behaviors","Red teaming","Scalable automation","Software 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If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.</p>\n<ul>\n<li>Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts</li>\n</ul>\n<ul>\n<li>Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)</li>\n</ul>\n<ul>\n<li>401(k) retirement plan with employer match</li>\n</ul>\n<ul>\n<li>Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)</li>\n</ul>\n<ul>\n<li>Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees</li>\n</ul>\n<ul>\n<li>13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)</li>\n</ul>\n<ul>\n<li>Mental health and wellness support</li>\n</ul>\n<ul>\n<li>Employer-paid basic life and disability coverage</li>\n</ul>\n<ul>\n<li>Annual learning and development stipend to fuel your professional growth</li>\n</ul>\n<ul>\n<li>Daily meals in our offices, and meal delivery credits as eligible</li>\n</ul>\n<ul>\n<li>Relocation support for eligible employees</li>\n</ul>\n<ul>\n<li>Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.</li>\n</ul>\n<p>More details about our benefits are available to candidates during the hiring process.</p>\n<p>This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.</p>\n<p><strong>About the Team</strong></p>\n<p>The Safety Systems team is dedicated to ensuring the safety, robustness, and reliability of AI models towards their deployment in the real world.</p>\n<p>OpenAI’s charter calls on us to ensure the benefits of AI are distributed widely. Our Health AI team is focused on enabling universal access to high-quality medical information. We work at the intersection of AI safety research and healthcare applications, aiming to create trustworthy AI models that can assist medical professionals and improve patient outcomes.</p>\n<p><strong>About the Role</strong></p>\n<p>We’re seeking strong researchers who are passionate about advancing AI safety and improving global health outcomes. As a Research Scientist, you will contribute to the development of safe and effective AI models for healthcare applications. You will implement practical and general methods to improve the behavior, knowledge, and reasoning of our models in these settings. This will require research into safety and alignment techniques that we aim to generalize towards safe and beneficial AGI.</p>\n<p>This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.</p>\n<p><strong>In this role, you will:</strong></p>\n<ul>\n<li>Design and apply practical and scalable methods to improve safety and reliability of our models, including RLHF, automated red teaming, scalable oversight, etc.</li>\n</ul>\n<ul>\n<li>Evaluate methods using health-related data, ensuring models provide accurate, reliable, and trustworthy information.</li>\n</ul>\n<ul>\n<li>Build reusable libraries for applying general alignment techniques to our models.</li>\n</ul>\n<ul>\n<li>Proactively understand the safety of our models and systems, identifying areas of risk.</li>\n</ul>\n<ul>\n<li>Work with cross-team stakeholders to integrate methods in core model training and launch safety improvements in OpenAI’s products.</li>\n</ul>\n<p><strong>You might thrive in this role if you:</strong></p>\n<ul>\n<li>Are excited about OpenAI’s mission of ensuring AGI is universally beneficial and are aligned with OpenAI’s charter.</li>\n</ul>\n<ul>\n<li>Demonstrate passion for AI safety and improving global health outcomes.</li>\n</ul>\n<ul>\n<li>Have 4+ years of experience with deep learning research and LLMs, especially practical alignment topics such as RLHF, automated red teaming, scalable oversight, etc.</li>\n</ul>\n<ul>\n<li>Hold a Ph.D. or other degree in computer science, AI, machine learning, or a related field.</li>\n</ul>\n<ul>\n<li>Stay goal-oriented instead of method-oriented, and are not afraid of unglamorous but high-value work when needed.</li>\n</ul>\n<ul>\n<li>Possess experience making practical model improvements for AI model deployment.</li>\n</ul>\n<ul>\n<li>Own problems end-to-end, and are willing to pick up whatever knowledge you&#39;re missing to get the job done.</li>\n</ul>\n<ul>\n<li>Are a team player who enjoys collaborative work environments.</li>\n</ul>\n<ul>\n<li>Bonus: possess experience in health-related AI research or deployments.</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. 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