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production systems serving millions of users.</p>\n<p>Embody our culture and values.</p>\n<p>Qualifications:</p>\n<p>Required Qualifications:</p>\n<p>Bachelor’s Degree in Computer Science, or related technical discipline AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.</p>\n<p>Preferred Qualifications:</p>\n<p>Bachelor’s Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR Master’s Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.</p>\n<p>Experience prompting and working with large language models.</p>\n<p>Experience writing production-quality Python code.</p>\n<p>Demonstrated interest in Responsible AI.</p>\n<p>Software Engineering IC4 – The typical base pay range for this role across the U.S. is USD $119,800 – $234,700 per year.</p>\n<p>Software Engineering IC5 – The typical base pay range for this role across the U.S. is USD $139,900 – $274,800 per year.</p>\n<p>This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.</p>\n<p>Microsoft is an equal opportunity employer.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a 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We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.</p>\n<p><strong>About the Team</strong></p>\n<p>The Frontier Red Team (FRT) is a small, focused technical research team within Anthropic&#39;s Policy organization. Our goal is to make the entire world safer in an era of advanced AI by understanding what these systems can do and building the defenses that matter.</p>\n<p>In 2026, we&#39;re focused on researching and ensuring safety with self-improving, highly autonomous AI systems, especially ones related to cyberphysical capabilities. See our previous related work on exploits, partnering with Mozilla, and zero days. 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This work sits at the intersection of AI capabilities research, cybersecurity, and policy—what we learn directly shapes how Anthropic and the world prepare for AI-enabled cyber threats.</p>\n<p>This is applied research with real-world stakes. 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However, some roles may require more time in our offices.</p>\n<p><strong>Visa sponsorship:</strong> We do sponsor visas! However, we aren&#39;t able to successfully sponsor visas for every role and every candidate. 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We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.</p>\n<p><strong>About the Team</strong></p>\n<p>The Frontier Red Team (FRT) is a small, focused technical research team within Anthropic&#39;s Policy organization. Our goal is to make the entire world safer in this era of advanced AI by understanding what these systems can do and building the defenses that matter.</p>\n<p>In 2026, we&#39;re focused on researching and ensuring safety with self-improving, highly autonomous AI systems—especially ones with cyberphysical capabilities. See our previous related work on cyberdefense, robotics, and Project Vend. This is early-stage, high-conviction research with the potential for outsized impact.</p>\n<p><strong>About the Role</strong></p>\n<p>Our team is focused on a critical question: how do we defend against a world where powerful, autonomous, self-improving AI systems may be used adversarially?</p>\n<p>As a Research Engineer on our team, you&#39;ll build and eval model organisms of autonomous systems and develop the defensive agents needed to counter them. This work sits at the intersection of AI capabilities research, security, and policy—what we learn directly shapes how Anthropic and the world prepare for advanced AI.</p>\n<p>This is applied research with real-world stakes. Your work will inform decisions at the highest levels of the company, contribute to public demonstrations that shape policy discourse, and help build technical defenses that could matter enormously as AI systems become more capable.</p>\n<p><strong>What You&#39;ll Do</strong></p>\n<ul>\n<li>Design and build autonomous AI systems that can use tools and operate across diverse environments—creating model organisms that help us understand and defend against advanced adversarial AI</li>\n</ul>\n<ul>\n<li>Create evals and training environments to understand and shape agent behavior in desirable ways</li>\n</ul>\n<ul>\n<li>Develop defensive agents that can detect, disrupt, or outcompete adversarial AI systems in realistic scenarios</li>\n</ul>\n<ul>\n<li>Interface Claude with hardware platforms (e.g. robotics, physical systems) to understand cyberphysical risks and defenses</li>\n</ul>\n<ul>\n<li>Translate technical findings into compelling demonstrations and artifacts that inform policymakers and the public</li>\n</ul>\n<ul>\n<li>Collaborate with external experts in cybersecurity, national security, and AI safety to scope and validate research directions</li>\n</ul>\n<p><strong>Sample Projects</strong></p>\n<ul>\n<li>Developing systems where Claude controls diverse hardware and robotics platforms simultaneously</li>\n</ul>\n<ul>\n<li>Creating attack-defend simulations (CTFs, wargames, adversarial games) to test defensive AI capabilities</li>\n</ul>\n<ul>\n<li>Designing and implementing RL environments for training defensive agents</li>\n</ul>\n<ul>\n<li>Pointing autonomous systems at real-world security challenges to characterize risks and develop mitigations</li>\n</ul>\n<p><strong>You May Be a Good Fit If You</strong></p>\n<ul>\n<li>Have strong software engineering skills, particularly in Python</li>\n</ul>\n<ul>\n<li>Have experience building and working with LLM-based agents or autonomous systems</li>\n</ul>\n<ul>\n<li>Are driven to find solutions to ambiguously scoped, high-stakes problems</li>\n</ul>\n<ul>\n<li>Design and run experiments quickly, iterating fast toward useful results</li>\n</ul>\n<ul>\n<li>Thrive in collaborative environments (we love pair programming!)</li>\n</ul>\n<ul>\n<li>Care deeply about AI safety and want your work to have real-world impact on how humanity navigates advanced AI</li>\n</ul>\n<ul>\n<li>Can own entire problems end-to-end, including both technical and non-technical components</li>\n</ul>\n<ul>\n<li>Are comfortable working on sensitive projects that require discretion and integrity</li>\n</ul>\n<p><strong>Strong Candidates May Also Have</strong></p>\n<ul>\n<li>Experience with reinforcement learning, self-play, or multi-agent systems</li>\n</ul>\n<ul>\n<li>Experience with robotics, hardware interfaces, or cyberphysical systems</li>\n</ul>\n<ul>\n<li>Track record of building demos or prototypes that communicate complex technical ideas</li>\n</ul>\n<ul>\n<li>Experience working with external stakeholders (policymakers, government, researchers)</li>\n</ul>\n<ul>\n<li>Familiarity with AI safety research and threat modeling for advanced AI systems</li>\n</ul>\n<p><strong>Logistics</strong></p>\n<p><strong>Education requirements:</strong> We require at least a Bachelor&#39;s degree in a related field or equivalent experience. <strong>Location-based hybrid policy:</strong> Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.</p>\n<p><strong>Visa sponsorship:</strong> We do sponsor visas! However, we aren&#39;t able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.</p>\n<p><strong>We encourage you to apply even if you do not believe you meet every single qualification.</strong> Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you&#39;re interested in this work. We think AI systems like the ones we&#39;re building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.</p>\n<p><strong>Your safety matters to us.</strong> 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 recruiters to help us find the best candidates for our open roles.</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_48f07618-377","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/5067100008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$320,000 - $850,000USD","x-skills-required":["Python","LLM-based agents","Autonomous systems","Reinforcement learning","Self-play","Multi-agent systems","Robotics","Hardware interfaces","Cyberphysical systems","AI safety research","Threat modeling"],"x-skills-preferred":["Software engineering","Collaborative environments","AI safety","Discretion and integrity"],"datePosted":"2026-03-08T13:45:56.349Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, LLM-based agents, Autonomous systems, Reinforcement learning, Self-play, Multi-agent systems, Robotics, Hardware interfaces, Cyberphysical systems, AI safety research, Threat modeling, Software engineering, Collaborative environments, AI safety, Discretion and integrity","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":320000,"maxValue":850000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_c1277210-c05"},"title":"Model Policy Manager, Chemical & Biological Risk","description":"<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>Safety Systems</p>\n<p><strong>Compensation</strong></p>\n<ul>\n<li>Estimated Base Salary $207K – $295K • 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. 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 at the forefront of OpenAI&#39;s mission to build and deploy safe AGI, driving our commitment to AI safety and fostering a culture of trust and transparency.</p>\n<p>The Model Policy team aligns model behavior with desired human values and norms. We co-design policy _with_ models and _for_ models by driving rapid policy taxonomy iteration based on data and defining evaluation criteria for foundational models’ ability to reason about safety. Key focus areas include: catastrophic risk, mental health, teen safety and multimodal safety.</p>\n<p><strong>About the Role</strong></p>\n<p>Providing access to frontier AI systems raises complex questions around dual-use science and catastrophic risk. How should models respond to requests involving chemical synthesis, biological experimentation, or pathogen research? Where is the boundary between legitimate scientific inquiry and information that could enable misuse? How do we design policies that meaningfully reduce risk without unnecessarily restricting beneficial research?</p>\n<p>This is a senior role in which you’ll help shape policy creation and development at OpenAI for addressing biological and chemical risks. You will develop structured policy frameworks and taxonomies to guide safe model behavior. This role sits at the intersection of biosecurity expertise, AI safety research, and policy design. You will help ensure that frontier AI systems can support beneficial life sciences research, such as drug discovery, public health, and biosafety, while reducing the risk that these capabilities could be misused.</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>In this role, you’ll:</p>\n<ul>\n<li>Design and maintain model policies governing chemical and biological risk, defining how models should safely handle dual-use scenarios.</li>\n<li>Develop structured taxonomies of chemical and biological risk that inform model training data, evaluation benchmarks, and safety monitoring systems.</li>\n<li>Translate biosecurity and chemical security expertise into actionable model behavior, working closely with research and engineering teams to operationalize policy in training and evaluation pipelines.</li>\n<li>Develop a broad range of subject matter expertise while maintaining agility across topics.</li>\n<li>Identify emerging risk vectors where frontier AI capabilities could meaningfully lower barriers to harmful activity and develop mitigation strategies.</li>\n<li>Engage with internal and external subject-matter experts in biosecurity, biodefense, and chemical safety to ensure policies reflect real-world risk landscapes.</li>\n</ul>\n<p>You might thrive in this role if you:</p>\n<ul>\n<li>Have strong domain expertise in chemistry, biology, biosecurity, or related fields and are motivated to translate that expertise into principled, operational policies that scale to frontier AI systems.</li>\n<li>Have experience researching or working with LLMs, machine learning, AI governance, technology policy, or related areas, and enjoy tackling structured reasoning and classification problems—such as defining boundaries between legitimate scientific inquiry and potentially harmful applications.</li>\n<li>Have experience designing, refining, or enforcing policies or safeguards for complex systems, whether in AI/ML environments, scientific research governance, national security contexts, or other high-stakes technical domains.</li>\n<li>Are comfortable navigating ambiguous, high-stakes problem spaces, balancing risk reduction with the benefits of scientific openness and innovation.</li>\n<li>Enjoy building new frameworks from first principles, reasoning about open-ended problems, and generating novel approaches under uncertainty. You take ownership of problems end-to-end—from defining the conceptual framework through collaborating with research and engineering teams</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_c1277210-c05","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/6df6a3d8-c72b-4e65-acf8-a5d91559533c","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$207K – $295K","x-skills-required":["chemistry","biology","biosecurity","AI safety research","policy design","machine learning","LLMs","AI governance","technology policy"],"x-skills-preferred":["structured reasoning","classification problems","policy creation","development","biosecurity expertise","chemical security expertise"],"datePosted":"2026-03-06T18:42:18.171Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"chemistry, biology, biosecurity, AI safety research, policy design, machine learning, LLMs, AI governance, technology policy, structured reasoning, classification problems, policy creation, development, biosecurity expertise, chemical security expertise","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":207000,"maxValue":295000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_28cb565e-69a"},"title":"Researcher, Health AI","description":"<p><strong>Researcher, Health AI</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>Safety Systems</p>\n<p><strong>Compensation</strong></p>\n<ul>\n<li>$295K – $445K • 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. 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. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. 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This includes enabling third party assessments for OpenAI’s flagship launches, piloting new assurance mechanisms like safety compliance reviews, and incorporating independent expert input as evidence for critical safety decisions. This role requires a blend of partnership management, cross functional coordination, an understanding of AI safety research and evaluations, and strong communication skills to synthesize findings and translate into decision relevant actions.</p>\n<p><strong>About the Role</strong></p>\n<p>As a Technical Program Manager on the Trustworthy AI team, you will drive interdisciplinary programs in collaboration with external partners. 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