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At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact , advancing our long-term goals of steerable, trustworthy AI , rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We&#39;re an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.</p>\n<p><strong>Come work with us!</strong></p>\n<p>Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.</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_450d2493-b50","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/5135168008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"CHF280,000-CHF680,000","x-skills-required":["Python","Deep learning frameworks","ML Accelerators","Kubernetes","Large-scale data processing"],"x-skills-preferred":["Software engineering","Machine learning research","Collaborative work","Communication skills"],"datePosted":"2026-04-18T15:43:14.925Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Zürich, CH"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, Deep learning frameworks, ML Accelerators, Kubernetes, Large-scale data processing, Software engineering, Machine learning research, Collaborative work, Communication skills","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":280000,"maxValue":680000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_aed77d7c-8f2"},"title":"Senior Counsel, Regulatory","description":"<p><strong>Senior Counsel, Regulatory</strong></p>\n<p>You will join Epic&#39;s regulatory team as a Senior Counsel, Regulatory. 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You will also assist with the company&#39;s response to regulatory investigations and requests for information from regulators.</p>\n<p><strong>Key Responsibilities</strong></p>\n<ul>\n<li>Advise Epic senior management, Product Counsel, the Compliance Team and Legal leadership on key global laws and regulations, including online safety frameworks</li>\n<li>Lead multi-stakeholder regulatory compliance strategies</li>\n<li>Provide legal analysis of legislative and regulatory drafts to the Public Policy team</li>\n<li>Support advocacy and engagement with regulators and trade associations</li>\n<li>Respond to global regulatory inquiries and investigations</li>\n</ul>\n<p><strong>Requirements</strong></p>\n<ul>\n<li>A qualified attorney with at least 8 years of experience working in regulatory compliance, either within a regulatory body, in-house or at a law firm</li>\n<li>If based outside of North America, the willingness and ability to consistently work US Eastern time zone hours</li>\n<li>Experience handling regulatory enforcement actions brought by regulatory bodies</li>\n<li>Prior work and/or substantial knowledge of the tech industry. 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This will in practice include:</p>\n<ul>\n<li>Setting north star goals and milestones for new research directions, and developing challenging evaluations to track progress.</li>\n</ul>\n<ul>\n<li>Personally driving or leading research in new exploratory directions to demonstrate feasibility and scalability of the approaches.</li>\n</ul>\n<ul>\n<li>Working horizontally across safety research and related teams to ensure different technical approaches work together to achieve strong safety results.</li>\n</ul>\n<p><strong>In this role, you will:</strong></p>\n<ul>\n<li>Set the research directions and strategies to make our AI systems safer, more aligned and more robust.</li>\n</ul>\n<ul>\n<li>Coordinate and collaborate with cross-functional teams, including the rest of the research organization, T&amp;S, policy and related alignment teams, to ensure that our AI meets the highest safety standards.</li>\n</ul>\n<ul>\n<li>Actively evaluate and understand the safety of our models and systems, identifying areas of risk and proposing mitigation strategies.</li>\n</ul>\n<ul>\n<li>Conduct state-of-the-art research on AI safety topics such as RLHF, adversarial training, robustness, and more.</li>\n</ul>\n<ul>\n<li>Implement new methods in OpenAI’s 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 building safe, universally beneficial AGI and are aligned with OpenAI’s charter</li>\n</ul>\n<ul>\n<li>Demonstrate a passion for AI safety and making cutting-edge AI models safer for real-world use.</li>\n</ul>\n<ul>\n<li>Bring 4+ years of experience in the field of AI safety, especially in areas like RLHF, adversarial training, robustness, fairness &amp; biases.</li>\n</ul>\n<ul>\n<li>Hold a Ph.D. or other degree in computer science, machine learning, or a related field.</li>\n</ul>\n<ul>\n<li>Possess experience in safety work for AI model deployment</li>\n</ul>\n<ul>\n<li>Have an in-depth understanding of deep learning research and/or strong engineering skills.</li>\n</ul>\n<ul>\n<li>Are a team player who enjoys collaborative work environments.</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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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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This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that&#39;s revolutionising AI applications. You&#39;ll work directly with leadership to shape the company&#39;s direction in the AI and simulation markets.</p>\n<p><strong>About the Role</strong></p>\n<p>We&#39;re building the next-generation Grounding Service that powers the latest AI applications—chat assistants, copilots, and autonomous agents—with factual, cited, and trustworthy responses. Our platform stitches together retrieval, reasoning, and real-time data so that large language models stay anchored to enterprise knowledge, the public web, and proprietary tools. As a team, we value curiosity, pragmatic rigor, and inclusive collaboration.</p>\n<p><strong>Accountabilities</strong></p>\n<ul>\n<li>Owns the science roadmap for grounding—including retrieval, re-ranking, attribution, and reasoning—driving initiatives from problem framing to production impact.</li>\n<li>Designs and evolves state-of-the-art retrieval and RAG orchestration across documents, tables, code, and images.</li>\n</ul>\n<p><strong>The Candidate we&#39;re looking for</strong></p>\n<p><strong>Experience:</strong></p>\n<ul>\n<li>Bachelor’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 2+ years related experience (e.g., statistics, predictive analytics, research) OR Master’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field OR equivalent experience.</li>\n</ul>\n<p><strong>Technical skills:</strong></p>\n<ul>\n<li>Solid coding skills and solid foundation in machine learning, with the ability to implement and optimize models effectively.</li>\n</ul>\n<p><strong>Personal attributes:</strong></p>\n<ul>\n<li>Demonstrated ability to lead through ambiguity, make principled trade-offs, and deliver measurable impact in cross-functional, fast-paced settings.</li>\n</ul>\n<p><strong>Benefits</strong></p>\n<ul>\n<li>Competitive salary and benefits package.</li>\n<li>Opportunities for professional growth and development.</li>\n<li>Collaborative and dynamic work environment.</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_5fca8c17-a2d","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Microsoft AI","sameAs":"https://microsoft.ai","logo":"https://logos.yubhub.co/microsoft.ai.png"},"x-apply-url":"https://microsoft.ai/job/applied-scientist-2-3/","x-work-arrangement":"hybrid","x-experience-level":"mid","x-job-type":"full-time","x-salary-range":"Competitive salary and benefits package","x-skills-required":["machine learning","statistics","predictive analytics","research"],"x-skills-preferred":["solid coding skills","principled trade-offs","collaborative work environment"],"datePosted":"2026-03-06T07:26:37.623Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Beijing"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"machine learning, statistics, predictive analytics, research, solid coding skills, principled trade-offs, collaborative work environment"}]}