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The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training.</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_465e2cfb-ddc","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Scale","sameAs":"https://scale.com/","logo":"https://logos.yubhub.co/scale.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/scaleai/jobs/4628044005","x-work-arrangement":"onsite","x-experience-level":"staff","x-job-type":"full-time","x-salary-range":"$264,800-$331,000 USD","x-skills-required":["large language model","NLP","Transformer modeling","evaluation methodologies","metrics","benchmarks","instruction following","factuality","robustness","fairness"],"x-skills-preferred":[],"datePosted":"2026-04-18T15:59:31.100Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA; Seattle, WA; New York, NY"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"large language model, NLP, Transformer modeling, evaluation methodologies, metrics, benchmarks, instruction following, factuality, robustness, fairness","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":264800,"maxValue":331000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_c1b40ca4-8d1"},"title":"Investment Banking Expert - M&A","description":"<p><strong>About the Role</strong></p>\n<p>We are seeking a skilled Investment Banking - M&amp;A Expert to enhance xAI&#39;s AI models by providing high-quality data annotations and inputs tailored to M&amp;A investment banking contexts.</p>\n<p>In this role, you will leverage your expertise in mergers, acquisitions, divestitures, financial modeling, valuation techniques, deal structuring, due diligence, pitch books, and fairness opinions to support the training of AI systems.</p>\n<p>You will collaborate with technical teams to refine annotation tools and curate impactful data, ensuring our models effectively capture real-world M&amp;A dynamics.</p>\n<p>This role requires adaptability, strong analytical skills, and a passion for driving innovation in a fast-paced environment.</p>\n<p><strong>Responsibilities</strong></p>\n<ul>\n<li>Utilize proprietary software to provide accurate input and labels for M&amp;A investment banking projects, ensuring high-quality data for AI model training.</li>\n<li>Deliver curated, high-quality data for scenarios involving mergers, acquisitions, divestitures, financial modeling, valuation techniques (e.g., DCF, comparables, precedent transactions), deal structuring, due diligence, pitch books, and fairness opinions.</li>\n<li>Collaborate with technical staff to support the training of new AI tasks and contribute to the development of innovative technologies.</li>\n<li>Assist in designing and improving efficient annotation tools tailored for M&amp;A investment banking data.</li>\n<li>Select and analyze complex problems in M&amp;A investment banking fields aligned with your expertise to enhance AI model performance.</li>\n<li>Interpret, analyze, and execute tasks based on evolving instructions, maintaining precision and adaptability.</li>\n</ul>\n<p><strong>Basic Qualifications</strong></p>\n<ul>\n<li>Professional experience in M&amp;A investment banking or related fields (e.g., M&amp;A advisor, analyst, associate, vice president or director in investment banking focused on mergers and acquisitions).</li>\n<li>Proficiency in reading and writing informal and professional English.</li>\n<li>Strong communication, interpersonal, analytical, and organizational skills.</li>\n<li>Excellent reading comprehension and ability to exercise autonomous judgment with limited data.</li>\n<li>Passion for technological advancements and innovation in M&amp;A investment banking.</li>\n</ul>\n<p><strong>Preferred Skills and Experience</strong></p>\n<ul>\n<li>Relevant certification or advanced training (e.g., Series 7, Series 63, Series 79, CFA, or similar finance-related certification).</li>\n<li>Experience mentoring or training others in M&amp;A investment banking practices, such as financial modeling, valuation, or deal execution.</li>\n<li>Comfort with recording audio or video sessions for data collection.</li>\n<li>Familiarity with AI or data annotation workflows in a technical setting.</li>\n</ul>\n<p><strong>Compensation and Benefits</strong></p>\n<p>US based candidates: $45/hour - $100/hour depending on factors including relevant experience, skills, education, geographic location, and qualifications. 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As a Research Scientist, you will apply and develop data and algorithmic cutting-edge solutions to advance our latest user-facing models. Your work will focus on advancing the safety and fairness behavior of state-of-the-art AI models, driving the development of foundational technology adopted by numerous product areas, including Gemini App, Cloud API, and Search.</p>\n<p>Key responsibilities include:</p>\n<ul>\n<li>Post-training/instruction tuning state-of-the-art LLMs, focusing on text-to-text, image/video/audio-to-text modalities and agentic capabilities</li>\n<li>Exploring data, reasoning, and algorithmic solutions to ensure Gemini Models are safe, maximally helpful, and work for everyone</li>\n<li>Improve Gemini&#39;s adversarial robustness, with a focus on high-stakes abuse risks</li>\n<li>Design and maintain high-quality evaluation protocols to assess model behavior gaps and headroom related to safety and fairness</li>\n<li>Develop and execute experimental plans to address known gaps, or construct entirely new capabilities</li>\n<li>Drive innovation and enhance understanding of Supervised Fine Tuning and Reinforcement Learning fine-tuning at scale</li>\n</ul>\n<p>To succeed as a Research Scientist in the Gemini Safety team, we look for the following skills and experience:</p>\n<ul>\n<li>PhD in Computer Science, a related field, or equivalent practical experience</li>\n<li>Significant LLM post-training experience</li>\n<li>Experience in Reward modeling and Reinforcement Learning for LLMs Instruction tuning</li>\n<li>Experience with Long-range Reinforcement learning</li>\n<li>Experience in areas such as Safety, Fairness, and Alignment</li>\n<li>Track record of publications at NeurIPS, ICLR, ICML</li>\n<li>Experience taking research from concept to product</li>\n<li>Experience with collaborating or leading an applied research project</li>\n<li>Strong experimental taste: Good judgment regarding baselines, ablations, and what is worth testing</li>\n<li>Experience with JAX</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_d2f5b1e5-545","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/7731944","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["PhD in Computer Science","LLM post-training experience","Reward modeling and Reinforcement Learning for LLMs Instruction tuning","Long-range Reinforcement learning","Safety, Fairness, and Alignment","NeurIPS, ICLR, ICML publications","Research from concept to product","Collaborating or leading an applied research project","JAX"],"x-skills-preferred":[],"datePosted":"2026-04-18T15:40:08.109Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Zurich, Switzerland"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"PhD in Computer Science, LLM post-training experience, Reward modeling and Reinforcement Learning for LLMs Instruction tuning, Long-range Reinforcement learning, Safety, Fairness, and Alignment, NeurIPS, ICLR, ICML publications, Research from concept to product, Collaborating or leading an applied research project, JAX"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_fbcb8138-106"},"title":"Investment Banking Expert - 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This requires a breadth of new ML research in the areas of human-AI collaboration, reasoning, robustness, and scalable oversight to keep pace with model capabilities.  We invest heavily in developing novel model and system-level methods of identifying and mitigating AI misuse and misalignment.</p>\n<p>Our goal is to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely.</p>\n<p><strong>About the Role</strong></p>\n<p>OpenAI is seeking a senior researcher with a passion for AI safety and experience in safety research. Your role will set directions for research to maintain effective oversight of safe AGI and work on research projects to identify and mitigate misuse and misalignment in our AI systems. You will play a critical role in defining how a safe AI system should look in the future at OpenAI, making a significant impact on our mission to build and deploy safe AGI.</p>\n<p>In this role, you will:</p>\n<ul>\n<li>Develop and refine AI monitor models to detect and mitigate known and emerging patterns of misuse and misalignment.</li>\n</ul>\n<ul>\n<li>Set research directions and strategies to make our AI systems safer, more aligned, and more robust.</li>\n</ul>\n<ul>\n<li>Evaluate and design effective red-teaming pipelines to examine the end-to-end robustness of our safety systems, and identify areas for future improvement.</li>\n</ul>\n<ul>\n<li>Conduct research to improve models’ ability to reason about questions of human values, and apply these improved models to practical safety challenges.</li>\n</ul>\n<ul>\n<li>Coordinate and collaborate with cross-functional teams, including T&amp;S, legal, policy and other research teams, to ensure that our products meet the highest safety standards.</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>Show enthusiasm for AI safety and dedication to enhancing the safety of cutting-edge AI models 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, human-AI collaboration, 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>Thrive in environments involving large-scale AI systems.</li>\n</ul>\n<ul>\n<li>Possess 4+ years of research engineering experience and proficiency in Python or similar languages.</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 mission is to develop user-first, privacy-preserving monetization products—including next-generation ads experiences—that strengthen user trust, unlock economic opportunity, and support OpenAI’s long-term innovation.</p>\n<p>Monetization plays a critical role in enabling OpenAI to continue pushing the boundaries of AI capabilities while ensuring the benefits of AGI are broadly shared. We believe monetization must be aligned with user value, uphold rigorous privacy and safety standards, and sustain a healthy ecosystem of developers and businesses.</p>\n<p>This team operates in a greenfield environment and moves quickly through prototyping, experimentation, and iterative deployment. We partner closely with Product, Design, and Research to bring research breakthroughs into real-world systems at global scale.</p>\n<p><strong>About the Role</strong></p>\n<p>We’re looking for an experienced Software Engineer to help build the core infrastructure behind OpenAI’s monetization and ads systems. In this foundational role, you’ll architect and implement distributed systems that power OpenAI’s monetization stack—focusing on reliability, performance, privacy, and large-scale operation.</p>\n<p>You’ll work across backend, systems, and platform layers to define and implement 0→1 infrastructure, partnering closely with Product, Design, and Research to shape the future of monetized AI experiences. Your work will enable both internal and external teams to build on safe, scalable, and robust monetization primitives.</p>\n<p>This role is exclusively based across our San Francisco &amp; Seattles sites. We offer relocation assistance to new employees.</p>\n<p><strong>In this role, you will:</strong></p>\n<ul>\n<li>Design and build the foundational backend and infrastructure powering OpenAI’s monetization and ads systems</li>\n</ul>\n<ul>\n<li>Architect large-scale distributed systems that meet strict requirements for reliability, privacy, security, and performance</li>\n</ul>\n<ul>\n<li>Develop APIs, infrastructure services, and internal platforms that support ads creation, delivery, measurement, and optimization</li>\n</ul>\n<ul>\n<li>Work closely with Product, Research, and Design to translate requirements into scalable technical solutions</li>\n</ul>\n<ul>\n<li>Drive 0→1 infra development through rapid prototyping, experimentation, and iterative improvements</li>\n</ul>\n<ul>\n<li>Contribute to the long-term technical strategy and roadmap for the monetization infra stack</li>\n</ul>\n<ul>\n<li>Ensure high engineering rigor through excellent testing, documentation, observability, and operational best practices</li>\n</ul>\n<ul>\n<li>Build for safety, privacy, fairness, and policy alignment from first principles</li>\n</ul>\n<ul>\n<li>Collaborate across engineering orgs to ensure the infra layer is flexible, performant, and resilient</li>\n</ul>\n<p><strong>You might thrive in this role if you:</strong></p>\n<ul>\n<li>Have 10+ years of experience building and operating large-scale distributed systems</li>\n</ul>\n<ul>\n<li>Have experience designing mission-critical systems with demanding reliability, performance, and correctness requirements</li>\n</ul>\n<ul>\n<li>Think in systems—architecture, data flows, operational concerns, observability, and long-term maintainability</li>\n</ul>\n<ul>\n<li>Are comfortable defining technical direction in ambiguous 0→1 environments</li>\n</ul>\n<ul>\n<li>Enjoy working cross-functionally to shape product requirements and system capabilities</li>\n</ul>\n<ul>\n<li>Communicate clearly, reason holistically, and make decisions grounded in user needs and long-term system health</li>\n</ul>\n<ul>\n<li>Bonus: Experience in ads systems, marketplaces, AI/ML infra, or other monetization-intensive domains</li>\n</ul>\n<p><strong>About OpenAI</strong></p>\n<p>OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. 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