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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_2bfc37e4-bc3"},"title":"Researcher, Pretraining Safety","description":"<p><strong>Job Posting</strong></p>\n<p><strong>Researcher, Pretraining Safety</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><strong>About the Team</strong></strong></p>\n<p>The Safety Systems team is responsible for various safety work to ensure our best models can be safely deployed to the real world to benefit the society and 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 Pretraining Safety team’s goal is to build safer, more capable base models and enable earlier, more reliable safety evaluation during training. We aim to:</p>\n<ol>\n<li><strong>Develop upstream safety evaluations</strong> that to monitor how and when unsafe behaviors and goals emerge;</li>\n</ol>\n<ol>\n<li><strong>Create safer priors</strong> through targeted pretraining and mid-training interventions that make downstream alignment more effective and efficient</li>\n</ol>\n<ol>\n<li><strong>Design safe-by-design architectures</strong> that allow for more controllability of model capabilities</li>\n</ol>\n<p>In addition, we will conduct the foundational research necessary for understanding how behaviors emerge, generalize, and can be reliably measured throughout training.</p>\n<p><strong><strong>About the Role</strong></strong></p>\n<p>The Pretraining Safety team is pioneering how safety is built into models before they reach post-training and deployment. In this role, you will work throughout the full stack of model development with a focus on pre-training:</p>\n<ul>\n<li>Identify safety-relevant behaviors as they first emerge in base models</li>\n</ul>\n<ul>\n<li>Evaluate and reduce risk without waiting for full-scale training runs</li>\n</ul>\n<ul>\n<li>Design architectures and training setups that make safer behavior the default</li>\n</ul>\n<ul>\n<li>Strengthen models by incorporating richer, earlier safety signals</li>\n</ul>\n<p>We collaborate across OpenAI’s safety ecosystem—from Safety Systems to Training—to ensure that safety foundations are robust, scalable, and grounded in real-world risks.</p>\n<p><strong><strong>In this role, you will:</strong></strong></p>\n<ul>\n<li>Develop new techniques to predict, measure, and evaluate unsafe behavior in early-stage models</li>\n</ul>\n<ul>\n<li>Design data curation strategies that improve pretraining priors and reduce downstream risk</li>\n</ul>\n<ul>\n<li>Explore safe-by-design architectures and training configurations that improve controllability</li>\n</ul>\n<ul>\n<li>Introduce novel safety-oriented loss functions, metrics, and evals into the pretraining stack</li>\n</ul>\n<ul>\n<li>Work closely with cross-functional safety teams to unify pre- and post-training risk reduction</li>\n</ul>\n<p><strong><strong>You might thrive in this role if you:</strong></strong></p>\n<ul>\n<li>Have experience developing or scaling pretraining architectures (LLMs, diffusion models, multimodal models, etc.)</li>\n</ul>\n<ul>\n<li>Are comfortable working with training infrastructure, data pipelines, and evaluation frameworks (e.g., Python, PyTorch/JAX, Apache Beam)</li>\n</ul>\n<ul>\n<li>Enjoy hands-on research — designing, implementing, and iterating on experiments</li>\n</ul>\n<ul>\n<li>Enjoy collaborating with diverse technical and cross-functional partners (e.g., policy, legal, training)</li>\n</ul>\n<ul>\n<li>Are data-driven with strong statistical reasoning and rigor in experimental design</li>\n</ul>\n<ul>\n<li>Value building clean, scalable research workflows and streamlining processes for yourself and others</li>\n</ul>\n<p><strong><strong>About OpenAI</strong></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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We are dedicated to identifying emerging abuse trends, analyzing risks, and working with our internal and external partners to implement effective mitigation strategies to protect against misuse. Our efforts contribute to OpenAI&#39;s overarching goal of developing AI that benefits humanity.</p>\n<p><strong>About the Role</strong></p>\n<p>As a Data Scientist, you will lead econometric and experimental analysis to understand how risk changes in complex human–AI systems. Your work will focus on measuring the magnitude and impact of risk shifts in a fast-paced, rapidly evolving operational environment. You will design experiments and observational studies to identify causal drivers and analyze changes in risk across a wide range of surfaces and sources. Your analyses will directly inform prioritization and strategic risk management across the company.</p>\n<p><strong>In this role, you will:</strong></p>\n<ul>\n<li>Own the design and execution of experimental and observational analyses used to assess strategic risk</li>\n</ul>\n<ul>\n<li>Develop econometric approaches to estimate the impact of product, policy, and external developments on key risk vectors</li>\n</ul>\n<ul>\n<li>Translate strategic risk questions into testable hypotheses and sound study designs</li>\n</ul>\n<ul>\n<li>Design and deploy A/B tests, as well as pseudo-experimental studies, to measure changes in risks and understand underlying mechanisms</li>\n</ul>\n<ul>\n<li>Identify, test, and explain product-driven, event-driven, or signal-driven changes in risk</li>\n</ul>\n<ul>\n<li>Establish baselines and statistical confidence around core metrics to size these problems</li>\n</ul>\n<ul>\n<li>Partner across teams to track strategic risks, identify opportunities for intervention, and develop analyses to evaluate those interventions</li>\n</ul>\n<p><strong>You might thrive in this role if you:</strong></p>\n<ul>\n<li>Have 3–6+ years in econometrics, causal inference, or experimental research</li>\n</ul>\n<ul>\n<li>Are comfortable owning ambiguous analyses with large-scale influence</li>\n</ul>\n<ul>\n<li>Are strong in experimental design, observational methods, and statistical reasoning</li>\n</ul>\n<ul>\n<li>Write solid Python and SQL</li>\n</ul>\n<ul>\n<li>Experience delivering zero-to-one analyses and scaling them from concept through deployment</li>\n</ul>\n<ul>\n<li>Communicate data-driven findings clearly, including uncertainty and trade-offs, to non-technical partners and leadership</li>\n</ul>\n<ul>\n<li>Nice to have: experience in trust and safety, integrity, operational security, intelligence analysis or other quantitative risk-focused 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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