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YubHub-native raw fields carry `x-` prefix.","jobs":[{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_5920f836-9df"},"title":"Manager, Machine Learning Research Scientist, GenAI","description":"<p>Scale AI accelerates the development of AI systems by providing data, infrastructure, and tooling that power advanced models. As AI evolves from static models to dynamic, agentic systems, Scale builds foundational research, evaluation methodologies, and agent/RL infrastructure.</p>\n<p>As a Research Scientist Manager, you will lead a world-class team of research scientists and engineers, defining the research roadmap and driving execution from early prototyping to deployment. You&#39;ll thrive in a fast-moving environment, balancing deep technical leadership with people management, vision setting, and delivery.</p>\n<p>Key responsibilities include:</p>\n<ul>\n<li>Leading, mentoring, and growing a team of research scientists and engineers working on GenAI research initiatives</li>\n<li>Defining and driving a multi-year research roadmap, identifying key scientific questions, setting milestones, allocating resources, and ensuring rigorous execution</li>\n<li>Collaborating cross-functionally with engineering, product, client-facing teams, and external academic or industry partners to translate research into components, insights, and actionable outcomes</li>\n<li>Communicating compellingly, publishing research, presenting at conferences, engaging in open-source contributions, and representing the team externally</li>\n<li>Driving an inclusive, high-performing culture, helping your team through technical challenges, providing growth opportunities, and attracting top talent</li>\n</ul>\n<p>Ideal candidates will have:</p>\n<ul>\n<li>5+ years of hands-on research experience in machine learning, deep learning, generative models, agent/RL systems, or related domains</li>\n<li>A strong track record of research excellence, including publications in top-tier ML/AI venues</li>\n<li>Experience leading or managing research teams, mentoring, coaching, and developing talent</li>\n<li>Excellent written and verbal communication skills, articulating research ideas and outcomes to technical and non-technical stakeholders</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_5920f836-9df","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Scale AI","sameAs":"https://scale.com/","logo":"https://logos.yubhub.co/scale.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/scaleai/jobs/4631811005","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$273,000-$393,000 USD","x-skills-required":["machine learning","deep learning","generative models","agent/RL systems","research leadership","team management","communication","publication","open-source contribution"],"x-skills-preferred":["PhD in machine learning or related domain","experience with large language models","post-training evaluation","agentic/RL environments"],"datePosted":"2026-04-18T16:00:09.239Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA; Seattle, WA; New York, NY"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"machine learning, deep learning, generative models, agent/RL systems, research leadership, team management, communication, publication, open-source contribution, PhD in machine learning or related domain, experience with large language models, post-training evaluation, agentic/RL environments","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":273000,"maxValue":393000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_536aa8eb-f7c"},"title":"Technical Influence Operations Threat Investigator","description":"<p>We are looking for a Technical Influence Operations Threat Investigator to join our Threat Intelligence team. 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This role may require responding to escalations during weekends and holidays.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Detect and investigate attempts to misuse Anthropic&#39;s AI systems for influence operations, including AI-generated disinformation, coordinated inauthentic behavior, astroturfing, and narrative manipulation campaigns</li>\n</ul>\n<ul>\n<li>Conduct technical investigations using SQL, Python, and other tools to analyze large datasets, trace user behavior patterns, and uncover coordinated networks of threat actors conducting influence operations</li>\n</ul>\n<ul>\n<li>Develop influence operation-specific detection capabilities, including abuse signals, behavioral clustering techniques, and detection methodologies tailored to AI-enabled information manipulation</li>\n</ul>\n<ul>\n<li>Create actionable intelligence reports on influence operation TTPs, emerging narrative threats, and threat actor campaigns leveraging AI systems</li>\n</ul>\n<ul>\n<li>Conduct cross-platform 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In this role, you&#39;ll lead crucial initiatives that directly impact our drug development portfolio, from developing sophisticated models for patient selection to creating AI-powered solutions for clinical trial optimization.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Lead and execute complex data science projects that directly advance our drug development portfolio</li>\n<li>Develop and implement sophisticated models for therapeutic hypothesis evaluation, including patient stratification and biomarker identification</li>\n<li>Design and create AI models for modernizing clinical trial evaluations, including surrogate endpoints</li>\n<li>Aid in the development and training of AI agents to automate and optimize biomedical workflows</li>\n<li>Collaborate cross-functionally with clinical, technical, and research teams</li>\n<li>Present complex analytical findings to senior stakeholders, including executive leadership</li>\n</ul>\n<p>About You:</p>\n<ul>\n<li>Required Qualifications:</li>\n</ul>\n<p>+ PhD in computational sciences or life sciences   + 3+ years of post-academic experience in life sciences (biotech, pharma, consulting)   + Strong programming skills, particularly in Python   + Extensive experience in multi-modal bioinformatics analysis</p>\n<ul>\n<li>Preferred Qualifications:</li>\n</ul>\n<p>+ Proven expertise in cloud computing environments, including proficiency with tabular and/or graph databases   + Strong background in machine learning and deep learning, particularly in biological applications   + Experience with large language models (LLM)   + Demonstrated ability to collaborate effectively with engineering teams on production systems   + Strong communication skills with proven ability to present complex technical findings to senior stakeholders</p>\n<p>Total Compensation Range: $170,000 - $215,000</p>\n<p>Where We Hire:</p>\n<p>Formation Bio is prioritizing hiring in key hubs, primarily the New York City and Boston metro areas, with a hybrid model requiring 3 days per week in office. Applicants from the Research Triangle (NC) and San Francisco Bay Area may also be considered.</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_54f58a4d-707","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Formation Bio","sameAs":"https://www.formation.bio/","logo":"https://logos.yubhub.co/formation.bio.png"},"x-apply-url":"https://job-boards.greenhouse.io/formationbio/jobs/6623947","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$170,000 - $215,000","x-skills-required":["PhD in computational sciences or life sciences","3+ years of post-academic experience in life sciences (biotech, pharma, consulting)","Strong programming skills, particularly in Python","Extensive experience in multi-modal bioinformatics analysis"],"x-skills-preferred":["Proven expertise in cloud computing environments, including proficiency with tabular and/or graph databases","Strong background in machine learning and deep learning, particularly in biological applications","Experience with large language models (LLM)","Demonstrated ability to collaborate effectively with engineering teams on production systems","Strong communication skills with proven ability to present complex technical findings to senior stakeholders"],"datePosted":"2026-04-18T15:53:58.264Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"New York, NY; Boston, MA"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Healthcare","skills":"PhD in computational sciences or life sciences, 3+ years of post-academic experience in life sciences (biotech, pharma, consulting), Strong programming skills, particularly in Python, Extensive experience in multi-modal bioinformatics analysis, Proven expertise in cloud computing environments, including proficiency with tabular and/or graph databases, Strong background in machine learning and deep learning, particularly in biological applications, Experience with large language models (LLM), Demonstrated ability to collaborate effectively with engineering teams on production systems, Strong communication skills with proven ability to present complex technical findings to senior stakeholders","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":170000,"maxValue":215000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_d1c3717f-844"},"title":"Biological Safety Research Scientist","description":"<p>We are seeking a Biological Safety Research Scientist to join our Safeguards team. 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You will be at the forefront of defining what responsible AI safety looks like in the biological domain, working across research, policy, and engineering to translate complex biosecurity concepts into concrete technical safeguards.</p>\n<p>Key responsibilities include:</p>\n<ul>\n<li>Design and execute capability evaluations to assess the capabilities of new models</li>\n<li>Collaborate closely with internal and external threat modeling experts to develop training data for our safety systems, and with ML engineers to train these safety systems, optimizing for both robustness against adversarial attacks and low false-positive rates for legitimate researchers</li>\n<li>Analyze safety system performance in traffic, identifying gaps and proposing improvements</li>\n<li>Develop rigorous stress-testing of our safeguards against evolving threats and product surfaces</li>\n<li>Partner with Research, Product, and Policy teams to ensure biological safety is embedded throughout the model development lifecycle</li>\n<li>Contribute to external communications, including model cards, blog posts, and policy documents related to biological safety</li>\n<li>Monitor emerging technologies for their potential to contribute to new risks and new mitigation strategies, and strategically address these</li>\n</ul>\n<p>You may be a good fit for this role if you have a PhD in molecular biology, virology, microbiology, biochemistry, systems or computational biology, or a related life sciences field, or equivalent professional experience. 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